Data · dataset · 2026
Figure 1 from Tumor-Secreted ADAMTSL4 Activates Latent TGFβ1 to Drive Cancer Cachexia
Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.1158/2159-8290.34040816
Description
<p>Circulating ADAMTSL4 levels are elevated in cancer cachexia. <b>A</b> and <b>B,</b> Relative body weight (BW) change (% of initial BW; <b>A</b>) and plasma ADAMTSL4 protein levels measured by ELISA (<b>B</b>) in cachectic C26 tumor-bearing mice (<i>n</i> = 8), noncachectic MC38 tumor-bearing mice (<i>n</i> = 10), and PBS-injected controls (<i>n</i> = 13). <b>C</b> and <b>D,</b> Relative BW change (<b>C</b>) and plasma ADAMTSL4 levels (<b>D</b>) in cachectic <i>Apc</i><sup>Min/+</sup> mice (<i>n</i> = 6) vs. wild-type (WT) littermates (<i>n</i> = 6). <b>E</b> and <b>F,</b> Relative BW change (<b>E</b>) and plasma ADAMTSL4 levels (<b>F</b>) in cachectic LLC tumor-bearing mice (<i>n</i> = 16) and PBS-injected controls (<i>n</i> = 11). <b>G,</b> Spearman correlation between plasma ADAMTSL4 levels and relative BW change across all mouse models (<i>n</i> = 70 XY pairs; pooled from <b>A–F</b>). <b>H</b> and <b>I,</b> Relative BW change (<b>H</b>) and circulating ADAMTSL4 levels (<b>I</b>; ELISA, log<sub>10</sub> scale) in noncachectic (non–cancer cachexia, <i>n</i> = 20) and cachectic (cancer cachexia, <i>n</i> = 27) patients with colorectal cancer. <b>J</b> and <b>K,</b> Spearman correlations in patients with colorectal cancer between circulating ADAMTSL4 levels and relative BW change (<b>J</b>; <i>n</i> = 47 XY pairs) or cachexia grade (<b>K</b>; <i>n</i> = 47 XY pairs). <b>L,</b> ROC analysis comparing circulating ADAMTSL4 with established cachexia-associated biomarkers in patients with colorectal cancer. <b>M</b> and <b>N</b>, Relative BW change (<b>M</b>) and circulating ADAMTSL4 protein levels (<b>N</b>) in noncachectic (<i>n</i> = 30) and cachectic (<i>n</i> = 14) patients with LUAD from the TRACERx cohort.
ADAMTSL4 was quantified by Olink proximity extension assay and is reported as NPX (log<sub>2</sub>-scaled relative abundance units). <b>O</b> and <b>P,</b> Spearman correlations between ADAMTSL4 NPX values and relative BW change (<b>O</b>; <i>n</i> = 44 XY pairs) or cachexia grade (<b>P</b>; <i>n</i> = 44 XY pairs) in patients with LUAD. <b>Q,</b> Kaplan–Meier analysis of OS in patients with NSCLC from the TRACERx cohort stratified by high vs. low circulating ADAMTSL4 (median NPX as cutoff). <b>R,</b> Kaplan–Meier analysis of disease-free survival in patients with NSCLC from the TRACERx cohort stratified by high vs. low circulating ADAMTSL4 (median NPX as cutoff).
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Data are presented as the mean ± SEM for mouse experiments (<b>A–F</b>). Relative BW change in patient cohorts (<b>H</b> and <b>M</b>) is shown with individual data points and mean ± SEM. For human biomarker group comparisons (<b>I</b> and <b>N</b>), data are shown as box-and-whisker plots with individual data points overlaid.
Boxes indicate the interquartile range, center lines indicate the median, and whiskers indicate Tukey whiskers (1.5 × IQR). ELISA-based ADAMTSL4 concentrations in patients with colorectal cancer (<b>I</b>) are shown on a log<sub>10</sub>-transformed scale, whereas circulating ADAMTSL4 levels in patients with LUAD (<b>N</b>) are presented as NPX values (log<sub>2</sub> scale). Due to differences in measurement platforms, values were analyzed within each cohort and were not directly compared across datasets. <i>Statistical analysis</i>: one-way ANOVA with Tukey multiple-comparisons test (<b>A</b> and <b>B</b>), two-tailed unpaired <i>t</i> test (<b>C–F</b>), and Spearman correlation (<b>G</b>).
Human data were systematically evaluated for normality and outliers (ROUT, Q = 1%). For ELISA-based comparisons in colorectal cancer (<b>I</b>), distributions were right-skewed; therefore, two-tailed Mann–Whitney tests were used as the primary analysis, with Welch <i>t</i> test on log<sub>10</sub>-transformed data performed as sensitivity analysis (see “Methods”). Group comparisons in patients (<b>H</b>, <b>I</b>, <b>M</b>, and <b>N</b>) were analyzed using two-tailed Mann–Whitney tests.
Correlation analyses in human cohorts (<b>J</b>, <b>K</b>, <b>O</b>, and <b>P</b>) were performed using two-tailed Spearman rank correlation. ROC analysis (<b>L</b>) was used to compare biomarker performance for discrimination of cachectic vs. noncachectic patients with colorectal cancer. Kaplan–Meier survival curves (<b>Q</b> and <b>R</b>) were compared using the log-rank (Mantel–Cox) test.
Significance is denoted as *, <i>P</i> < 0.05; ***, <i>P</i> < 0.001; ****, <i>P</i> < 0.0001; ns, not significant.</p>
Links
Where it is published
- DOI doi.org/10.1158/2159-8290.34040816 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
- From keywords
- Cancer · Cancer · Cancer · Earth & Environmental Science · Earth & Environmental Science · Earth & Environmental Science · Life Sciences · Life Sciences · Life Sciences · Medicine & Health · Medicine & Health · Medicine & Health
- Inferred from text
- Oncology and carcinogenesis 71%
Provenance · 3 source records, 17 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ZivaHub | oai:figshare.com:article/34040816 | 8 d ago | JSON v1 |
| Deakin Research Online | oai:figshare.com:article/34040816 | 8 d ago | JSON v1 |
| DMU Figshare | oai:figshare.com:article/34040816 | 8 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
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| concepts[disease].local:disease:cancer | mapping · figshare dmu ac uk | vocabulary-mapper@1.0.0 | keywords['Cancer'] |
| concepts[disease].local:disease:cancer | mapping · dro deakin edu au | vocabulary-mapper@1.0.0 | keywords['Cancer'] |
| concepts[field].anzsrc:group:3211 | enrichment · zivahub uct ac za | taxonomy-embedding@1.1.0 | title+keywords+description (71%) |
| concepts[field].local:field:earth-environmental | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
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| concepts[field].local:field:life-sciences | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
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| concepts[field].local:field:life-sciences | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| description | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/description |
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| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |