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Figure 1 from Tumor-Secreted ADAMTSL4 Activates Latent TGFβ1 to Drive Cancer Cachexia Juliano Machado (25154222) Vignesh Karthikaisamy (25154225) Hermine Mohr (25154228) Doris Kaltenecker (25154231) Pia Benedikt (25154234) Pauline Morigny (25154237) Amit Mhamane (25154240) Julia Geppert (25154243) Amy Rose Fumo (25154246) Kerstin Haase (14123058) Estefania Simoes (25154249) Joanna D.C.C. Lima (18725115) Anastasia Georgiadi (25154252) Achim Krüger (25154255) José Pinhata Otoch (25154258) Marc E. Martignoni (25154261) Vickie E. Baracos (25154264) Mariam Jamal-Hanjani (15386766) Marilia C.L. Seelaender (25154267) Olga Prokopchuk (25154270) Julia Szendrödi (25154273) Maria Rohm (25154276) Stephan Herzig (25154279) Mauricio Berriel Diaz (15037094) Cancer Molecular and Cellular Biology Gastrointestinal Cancers Colorectal cancer Lung Cancer Metabolism Metabolic pathways <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>^Min/+ 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, log₁₀ 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 (log₂-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). 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 log₁₀-transformed scale, whereas circulating ADAMTSL4 levels in patients with LUAD (<b>N</b>) are presented as NPX values (log₂ 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 log₁₀-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> 2026-10-01T00:00:00Z Image Figure 10.1158/2159-8290.34040816 https://figshare.com/articles/figure/Figure_1_from_Tumor-Secreted_ADAMTSL4_Activates_Latent_TGF_1_to_Drive_Cancer_Cachexia/34040816 CC BY