Otopetrin 1 protects against adipose tissue wasting during cancer cachexia progression

Summary

Cancer cachexia is a systemic metabolic disorder, with body weight loss and adipose tissue wasting as key features, and adipose tissue remodeling often preceding weight loss. Using pre-cachexia and cachexia models in Lewis lung carcinoma (LLC) tumor-bearing mice, transcriptomic analysis of white adipose tissue (WAT) identified Otopetrin 1 (Otop1) as a dynamically regulated gene, increased in pre-cachexia and decreased in cachexia. In patients with cancer, OTOP1 expression in subcutaneous WAT was reduced in cachexia and positively correlated with BMI in cachectic patients. In adipocytes treated with tumor-conditioned medium, OTOP1 overexpression alleviated metabolic dysfunction, accompanied by suppression of NF-κB signaling and activation of PPARγ, leading to reduced lipolysis and enhanced adipogenesis; these effects were partially attenuated by the PPARγ antagonist. Moreover, overexpression of OTOP1 in adipose tissue of LLC tumor-bearing mice alleviated adipose tissue wasting and improved lipid metabolism. These findings suggest a role for OTOP1 in adipose tissue remodeling during cancer cachexia.

Graphical abstract

Highlights

• •Early adipose inflammation and metabolic remodeling drive cachexia progression
• •OTOP1 is an underexplored regulator of adipose loss in cancer cachexia
• •Reduced OTOP1 in human scWAT associates with BMI and nutritional decline
• •OTOP1 protects against adipose wasting partly via NF-κB/PPARγ signaling

Endocrinology; oncology; human metabolism

Introduction

Cancer cachexia represents a systemic metabolic dysregulation, with progressive loss of skeletal muscle and adipose tissue as major features, accompanied by metabolite disturbances.¹ This condition leads to unintended weight loss and is associated with more than 20% of cancer-related mortality.² Nonetheless, standardized treatments are lacking.³ The international consensus categorizes the progression of cachexia into three distinct stages: pre-cachexia, cachexia, and refractory cachexia.^4,5 The pre-cachexia stage is considered an early phase marked by metabolic and clinic alterations without significant weight loss,⁶ whereas patients in the cachexia phase undergo muscle and adipose depletion, accompanied by systemic inflammation.^7,8 In the refractory cachexia stage, patients demonstrate a poor treatment response, with the median survival period less than 3 months.⁹ Because most patients with refractory cachexia are physically frail and unable to tolerate standard-dose anticancer therapies, early intervention for cachexia is therefore critically important.⁶

Adipose tissue loss, regardless of overall body weight, is an adverse prognostic factor in refractory cachexia.¹⁰ In patients with pancreatic ductal adenocarcinoma, those presenting with isolated adipose tissue depletion have a significantly higher risk of mortality compared with patients without wasting.¹¹ These findings highlight the important clinical significance of adipose tissue depletion in the progression of cachexia. Therefore, restoring cachexia-associated lipid metabolism abnormalities represents a promising therapeutic strategy.¹² Previous studies have identified multiple inflammatory mediators involved in adipose tissue remodeling during cachexia, including interleukin-6 (IL-6), parathyroid hormone-related protein (PTHrP), interferon-γ (IFN-γ), tumor necrosis factor alpha (TNF-α), zinc-α2-glycoprotein (ZAG), and growth/differentiation factor-15 (GDF-15). These factors accelerate adipose tissue depletion primarily by promoting lipolysis.^{13,14,15,16,17,18} Adipose triglyceride lipase (ATGL), an essential enzyme in lipolysis, has been demonstrated to be pivotal in this mechanism.¹⁹ Knocking out Atgl improves lipolysis in cachectic mice.²⁰ Alongside lipolysis, the augmented browning of white adipose tissue (WAT) is regarded as a crucial process contributing to adipose loss in cachexia.²¹ However, the role of uncoupling protein 1 (UCP1) expression in cachexia-associated adipose tissue has shown inconsistent findings. Some studies report increased Ucp1 expression and propose that it is regulated by various inflammatory factors and signaling pathways, including IL-6, PTHrP, and immune-sympathetic nervous system interactions.^22,23,24 Michaelis et al. demonstrated that in a mouse model of pancreatic cancer-associated cachexia, UCP1 levels were decreased, correlating with intensified central and peripheral inflammation, anemia, and alterations in circulating testosterone levels.²⁵ Importantly, Ucp1-deficient mice still develop cachexia and adipose tissue atrophy,²⁶ suggesting that UCP1-mediated thermogenesis may not be the primary driver of adipose catabolism. Nevertheless, effective therapeutic strategies targeting lipid metabolic abnormalities in adipose tissue during cachexia remain limited, and the underlying regulatory mechanisms require further investigation.

Otopetrins represent a class of proton-selective channels, with otopetrin 1 (OTOP1) playing a vital role in the development of gravity-sensing otoliths in the vestibular system and the perception of sour taste.^27,28,29 Previous research has demonstrated that OTOP1 is not only expressed in the inner ear and taste cells but is also highly expressed in brown adipose tissue (BAT).³⁰ Mice deficient in Otop1 display hypothermia and a diminished metabolic state during fasting, presumably resulting from a decreased ability for acute fuel mobilization.³¹ Wang et al. reported a significant increase of Otop1 in WAT of obese mice. Moreover, the Otop1 A151E mutation promotes macrophage polarization toward a pro-inflammatory phenotype in adipose tissue, leading to adipocyte death and increased local inflammation.³² In cachexia, a marked increase in pro-inflammatory cytokines has been shown to be accompanied by a shift in energy utilization.³³ Considering the emerging roles of OTOP1 in anti-inflammatory regulation and metabolic homeostasis, its potential involvement in adipose tissue remodeling during cachexia remains unclear.

Therefore, early intervention before significant body weight loss may be critical for improving cachexia outcomes. Identifying key regulatory factors involved in adipose tissue remodeling during cachexia is of particular importance. To address this issue, we established mouse models representing pre-cachexia and cachexia stages and performed transcriptomic analysis of inguinal WAT (iWAT) to screen for candidate genes. Our analysis identified OTOP1 as a candidate factor potentially involved in adipose tissue remodeling during cancer cachexia, whose role in this context has not been previously reported. We therefore further investigated whether and how OTOP1 contributes to adipose tissue metabolic alterations during cancer cachexia.

Results

Characterization of mouse models in the pre-cachexia and cachexia stages of cancer

As previously described,²³ Lewis lung carcinoma (LLC) cells readily form tumors and induce cachexia in C57BL/6 mice. We established the corresponding mouse models for this study (Figure 1A). Consistent with previous studies,^7,23 pre-cachexia and cachexia were operationally defined based on tumor-free body weight and metabolic parameters. Day 7 after tumor implantation, when no significant body weight loss or metabolic alterations were observed, was defined as the pre-cachexia stage. In contrast, day 21, characterized by marked body weight loss and metabolic dysfunction, was defined as the cachexia stage. To support this classification, metabolic cage analyses were performed. Oxygen consumption (VO₂) and carbon dioxide production (VCO₂) began to change at days 8–9 after tumor implantation (Figure S1). At the cachexia stage, VO₂ and VCO₂ were modestly increased during the light phase compared with controls, while the respiratory exchange ratio (RER) decreased compared with controls, indicating a shift toward lipid oxidation (Figures S2A–S2C). Locomotor activity showed no significant difference between groups at days 7–9 after tumor implantation but was markedly reduced at the cachexia stage (Figures S1D and S2D).

Figure 1.

Characterization of pre-cachexia and cachexia mouse models

(A) Schematic of the establishment of pre-cachexia and cachexia mouse models.

(B) Tumor-free body weight of mice, calculated by subtracting tumor weight from the total body weight (Day 7, n = 7:9; Day 21, n = 9:9).

(C) Weights of iWAT and eWAT in LLC xenograft mice versus non-tumor control mice (Day 7, n = 7:9; Day 21, n = 9:9).

(D and E) mRNA levels in iWAT of mice in the pre-cachexia (n = 7:8) (D) and cachexia (n = 6–7) (E) phases, quantified by RT-qPCR.

(F) Western blot analysis of UCP1 and HSP90 in iWAT during the pre-cachexia and cachexia phases, with HSP90 as the loading control (n = 4).

(G) Representative H&E staining showing morphological alterations in iWAT of LLC xenograft and control mice; representative immunofluorescence (IF) images of beige adipocytes labeled by UCP1 (green) and lipid droplets labeled by PLIN1 (red) in iWAT. From left to right: H&E, UCP1, PLIN1, UCP1/PLIN1 merged (scale bars: H&E, 100 μm; IF, 50 μm). n = 4 for each group. Data are mean ± SEM of biologically independent samples. Statistical significance was assessed by unpaired two-sided Student’s t test. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

With tumor progression, tumor weight in the cachexia group was markedly greater than that in the pre-cachexia group (Figure S3A). During the pre-cachexia phase, no significant difference in tumor-free body weight was observed between tumor-bearing and control mice; however, at the cachexia phase, tumor-bearing mice exhibited a 16.9% reduction in tumor-free body weight compared with controls (Figure 1B). Moreover, iWAT and epididymal white adipose tissue (eWAT) mass were reduced by 55.8% and 51.1%, respectively (Figure 1C), indicating progressive adipose tissue wasting. Food intake was not decreased at the pre-cachexia stage (Figure S1E) and remained comparable to controls during the cachexia stage (Figure S2E), suggesting that body weight loss was not associated with reduced food intake. We also measured the plasma lipid levels in mice at two stages. Except for an increase in high-density lipoprotein cholesterol (HDL-c) in the pre-cachexia group, no significant differences were observed in triglycerides (TG) or total cholesterol (TC) between the stages (Figures S3B–S3E).

Research indicates that the loss of subcutaneous WAT (scWAT) is more pronounced than that of visceral white adipose tissue (vWAT) in patients with cancer cachexia. Furthermore, scWAT mass serves as an independent prognostic factor in these patients.^34,35 Given these findings, we focused our analysis on scWAT to assess the expression of genes related to thermogenesis, inflammation, adipogenesis, and lipolysis during the pre-cachexia and cachexia phases (Figures 1D and 1E). The classic thermogenic gene Ucp1 was upregulated in the pre-cachexia phase but showed no significant change during cachexia. Genes related to adipogenesis and lipolysis exhibited no notable changes in the pre-cachexia phase; however, adipogenesis was downregulated and lipolysis was upregulated during cachexia. H&E staining, immunofluorescence, and western blot analysis revealed smaller lipid droplets and increased UCP1 expression in the pre-cachexia phase. However, in the cachexia phase, lipid droplets remained small, whereas UCP1 expression did not show significant changes (Figures 1F and 1G). These findings suggest that tumor progression is accompanied by metabolic alterations in mice, including enhanced lipolysis and a transient increase in WAT browning in our model.

Differentially expressed genes and pathways in WAT during the pre-cachexia stage

We further analyzed the shared and distinct signaling pathways altered in mouse iWAT during progression of cancer cachexia. RNA sequencing was conducted to analyze the transcriptomes of iWAT from tumor-bearing and non-tumor groups during the pre-cachexia phase, revealing differentially expressed genes (DEGs) and altered signaling pathways. DEGs were selected with a fold change >1.5 and a false discovery rate (FDR) <0.05. The volcano plot indicates that during the pre-cachexia period, there were relatively few DEGs between the tumor-bearing and non-tumor groups, with 43 genes upregulated and only one downregulated (Figure 2A). To explore the biological functions of the DEGs, Gene Ontology (GO) enrichment analysis was performed. The biological process (BP) GO terms indicated that, during pre-cachexia, key pathways involved immune responses, response to stimuli, and cytokine signaling (Figure 2B). The enrichment of molecular function (MF) and cellular component (CC) terms highlighted associations with lipid binding, oxygen binding, oxygen carrier activity, peroxidase activity, CXCR chemokine receptor binding, and mitochondria (Figure 2C; Figure S4A). These findings suggest that lipid metabolism and oxygen supply-demand regulation in WAT may be altered during the pre-cachexia phase, with the tissue potentially exhibiting changes in oxygen transport capacity.

Figure 2.

DEGs and pathways in iWAT during the pre-cachexia phase of cancer cachexia

(A) Volcano plot of DEGs in iWAT from tumor and non-tumor groups during the pre-cachexia phase (FDR < 0.05, fold change > 1.5) (top). Red dots represent upregulated DEGs, and orange dots represent downregulated DEGs (n = 4:5). Number of DEGs in iWAT between tumor and non-tumor groups in the pre-cachexia phase: 43 genes were upregulated, and one gene was downregulated (bottom).

(B and C) GO enrichment analysis of DEGs, depicting the BP (B) and MF (C) categories.

(D) KEGG pathway enrichment analysis of DEGs, showing the top 15 significantly enriched pathways.

(E) Representative GSEA enrichment plots of four key pathways in the pre-cachexia phase.

(F) GSEA of the top 10 upregulated (red, right) and downregulated (blue, left) pathways during the pre-cachexia phase, ranked by NES.

GO, Gene Ontology; BP, biological process; MF, molecular function; GSEA, gene set enrichment analysis; NES, normalized enrichment score.

Mapping the DEGs to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed that, in the pre-cachexia phase of cancer, significantly altered pathways encompassed inflammatory and immune-related pathways, including cytokine-cytokine receptor interaction, NOD-like receptor signaling, and the TNF signaling pathways. Furthermore, processes associated with lipid metabolism, such as the PPAR signaling pathway and fatty acid elongation, were also impacted (Figure 2D; Figures S4B–S4D). The top ten enriched pathways from gene set enrichment analysis (GSEA) also revealed significant changes in relevant pathways (Figure 2F). Specifically, the cytokine-cytokine receptor interaction, chemokine signaling, PPAR signaling, and NOD-like receptor signaling pathways were notably enriched (Figure 2E). Collectively, these findings indicate that while pathways directly associated with WAT atrophy remain unaltered during the pre-cachexia phase, there is evidence of metabolic remodeling and partial inflammatory activation at the transcriptional level.

DEGs and pathways in WAT during the cachexia stage

We next investigated alterations in iWAT during the cancer cachexia phase, which is associated with marked body weight loss, focusing on DEGs and signaling pathways. During this phase, the number of DEGs was significantly higher than that observed in the pre-cachexia phase. A volcano plot illustrated the distribution of DEGs, with 778 genes significantly upregulated and 241 downregulated in the tumor-bearing group (Figure 3A). GO term enrichment analysis revealed that, in the BP category, enriched pathways pertained to translation, peptide and amide metabolism, ribosome biogenesis, and positive regulation of cell motility (Figure 3B). In the MF and CC categories, enriched terms included cytokine receptor activity, immune receptor activity, ribosomal structure, protein/glycosaminoglycan binding, and ubiquitin-related activity (Figure 3C; Figure S5A). These findings indicate that, during the cachexia phase, adipose tissue displays transcriptional alterations associated with protein metabolism, inflammatory signaling, and extracellular matrix organization. Notably, the enrichment of synaptic translation-related pathways may reflect changes in neuronal-associated processes within adipose tissue.

Figure 3.

Identification of DEGs and functional enrichment analysis in iWAT during cancer cachexia

(A) Volcano plot of DEGs in iWAT from tumor-bearing and non-tumor groups during the cachexia phase (FDR < 0.05, fold change > 1.5) (top). Red dots represent upregulated DEGs, and orange dots represent downregulated DEGs (n = 4:5). Number of DEGs in iWAT during the cachexia phase: 778 genes were upregulated, and 241 genes were downregulated (bottom).

(B and C) GO enrichment analysis of DEGs during the cachexia phase, categorized by BP (B) and MF (C).

(D) KEGG pathway mapping of DEGs, highlighting the top 15 most significantly enriched pathways.

(E) Representative GSEA enrichment plots of four key pathways during the cachexia phase.

(F) GSEA identifying the top 12 upregulated and downregulated pathways in cancer cachexia, ranked by NES. Upregulated pathways shown in red (right) and downregulated pathways in blue (left).

GO, Gene Ontology; BP, biological process; MF, molecular function; GSEA, gene set enrichment analysis; NES, normalized enrichment score.

KEGG pathway analysis of DEGs demonstrated considerable enrichment in pathways including PPAR signaling, cytokine-cytokine receptor interaction, regulation of lipolysis, leukocyte transendothelial migration, and calcium signaling (Figure 3D). These findings suggest accelerated energy and functional depletion in WAT. Unlike in the pre-cachexia phase, where the PPAR signaling pathway is upregulated, it is downregulated during the cachexia phase (Figures 3D and 3E; Figure S5B). In the pre-cachexia phase, adipose tissue may attempt to sustain energy metabolism and anti-inflammatory capacity, potentially associated with the upregulation of the PPAR signaling pathway observed at the transcriptional level. The subsequent downregulation during cachexia may reflect metabolic dysregulation and a deterioration of tissue function. The PPAR signaling pathway likely plays a pivotal role in the interplay between inflammation and metabolism: inflammation inhibits PPAR signaling and impairs adipose metabolism, while downregulation of PPAR signaling further exacerbates inflammation, establishing a detrimental cycle.³⁶

GSEA enrichment analysis of the top 12 pathways indicated downregulation of carbon metabolism, the tricarboxylic acid (TCA) cycle, pyruvate metabolism, fatty acid metabolism, and branched-chain amino acid degradation, suggesting impaired mitochondrial function in adipose tissue and dysregulated lipid and glucose metabolism (Figures 3E and 3F; Figure S5B). The downregulation of retinol metabolism and the glyoxylate and dicarboxylate cycle indicates that adipose tissue may lose its capacity to sustain normal metabolic processes. Conversely, the upregulation of the NF-κB signaling pathway and cytokine-cytokine receptor interaction indicates an exacerbated inflammatory response, with widespread gene activation observed in these pathways (Figure 3E; Figures S5C and S5D). Enhanced Th17 cell differentiation likely reflects active participation of adipose tissue in the recruitment and regulation of immune cells. In summary, during cachexia, WAT shifts from an energy storage organ to a major contributor to systemic inflammation, becoming profoundly involved in the systemic inflammatory process.

These results suggest that in the early stages of cachexia, inflammation and adaptive metabolism are prominent features, with the upregulation of the PPAR signaling pathway likely contributing to early adaptive maintenance. As cachexia advances, the PPAR pathway is downregulated, while the NF-κB signaling pathway is significantly upregulated. Additionally, pathways involved in energy, amino acid, and lipid metabolism are downregulated, suggesting metabolic impairment and increased inflammatory activation in WAT. Collectively, these findings indicate that adipose tissue may play an increasingly important role in systemic inflammation and metabolic dysregulation during cancer cachexia.

Otop1 in WAT is a candidate factor involved in adipose tissue remodeling during cachexia

To identify key regulatory factors in WAT during the progression of cachexia, we first screened for genes altered in both the pre-cachexia and cachexia phases. This aimed to highlight signals likely driven persistently by tumors. We conducted an intersection analysis of DEGs from the tumor-bearing and non-tumor groups in the pre-cachexia stage, as well as from the cachexia stage. This analysis identified 13 key genes that exhibit sustained changes across both stages (Figures 4A and 4B). Among them, six genes are related to heme and platelet function (Alas2, Selp, Hbb, Hba, etc.), while others are involved in inflammation and chemotaxis, including Cxcr2, Il-4Rα, and caspase-4. In addition, Ctla2a, Cd300lf, and Tent5C are primarily associated with immune responses and viral defense. Otop1 has been reported to be highly expressed in BAT³⁰ and can be induced in obesity models, where it alleviates adipose tissue inflammation and protects mice from obesity-related metabolic dysfunction.³²

Figure 4.

Transcriptomic identification of candidate genes associated with adipose tissue remodeling during cachexia progression

(A and B) Venn diagram (A) showing the overlap of DEGs between pre-cachexia (Day 7-LLC vs. Day 7-PBS) and cachexia (Day 21-LLC vs. Day 21-PBS) tumor-bearing mice. 13 genes were consistently altered across both stages. (B) Heatmap showing the expression profiles of these 13 shared DEGs in pre-cachexia (left) and cachexia (right) groups.

(C and D) Venn diagram (C) illustrating the intersection between the 13 genes from (A) and DEGs from Day 7-LLC vs. Day 21-LLC comparison, aiming to identify genes that change with tumor progression. Three genes were retained. (D) Heatmap showing their expression patterns in Day 7-LLC and Day 21-LLC.

(E) Venn diagram identifying genes upregulated in Day 7-LLC vs. Day 7-PBS and downregulated in Day 21-LLC vs. Day 21-PBS. Otop1 is the only overlapping gene.

(F) qPCR validation of Otop1 expression in iWAT from tumor-bearing and control mice during pre-cachexia and cachexia phases (pre-cachexia, n = 6:8; cachexia, n = 6:7). Data are presented as mean ± SEM. Statistical significance was determined using an unpaired two-sided Student’s t test, with p < 0.05 considered significant.

Second, we compared gene expression exclusively between the two tumor groups (Day 7-LLC vs. Day 21-LLC, FDR < 0.5) to further narrow the candidates, by retaining only those genes whose expression changed as the tumor progressed (Figures 4C and 4D). This analysis yielded three remaining candidates: Otop1, Ctla2a, and Selp.

We hypothesize that key genes governing cachexia-associated adipose loss are upregulated during the pre-cachexia phase, potentially contributing to the maintenance of adipose tissue homeostasis. However, during the cachexia phase, these genes are downregulated and lose their protective function, leading to exacerbated lipolysis. To test this hypothesis, we conducted an intersection analysis of the genes upregulated in the pre-cachexia tumor group and downregulated in the cachexia tumor group, identifying Otop1 as a candidate (Figure 4E). This result was further validated by qPCR (Figure 4F). Given its close association with both adipose metabolism and inflammation, we propose that Otop1 may play a pivotal role in the progression of adipose loss during cancer cachexia.

OTOP1 expression in scWAT correlates with the maintenance of nutritional status in patients with cancer

We next examined the relationship between OTOP1 expression in adipose tissue and BMI in human subjects to assess its relevance at the population level. scWAT samples were collected from 50 patients with cancer at the First Affiliated Hospital of Wenzhou Medical University. The clinical characteristics of the patients are summarized in Table S1. Among individuals with cancer, those who met the 2023 Asian diagnostic criteria of cachexia³⁷ were classified as experiencing cachexia, defined by weight loss >2% within 3–6 months or BMI <21 kg/m², together with one or more of the following: presence of anorexia, reduced grip strength, or elevated C-reactive protein (CRP) levels. Those who did not meet these criteria were categorized as non-cachexia. We measured OTOP1 gene expression levels in scWAT and found that OTOP1 levels were significantly lower in patients with cachexia compared to patients without cachexia (Figure 5A). Interestingly, within the group of patients with cachexia, OTOP1 expression showed a positive correlation with BMI (Figure 5B, R = 0.531, p = 0.008), suggesting that higher OTOP1 expression is closely associated with the maintenance of body weight in these patients. No such correlation was observed in patients without cachexia (Figure 5C). Further analysis revealed that when clinical indicators, including nutritional markers such as albumin (Alb) and hemoglobin (Hb), as well as the inflammatory marker CRP, were categorized into normal and abnormal value groups, OTOP1 levels were significantly lower in patients with below-normal Alb and Hb levels compared to those with normal levels (Figures 5D–5F). These findings suggest a strong association between OTOP1 expression and the nutritional status of patients with cancer cachexia.

Figure 5.

High OTOP1 expression in scWAT is associated with preservation of nutritional status in patients with cancer

OTOP1 levels were measured in scWAT samples from patients with cancer.

(A) OTOP1 expression in scWAT obtained from individuals with cancer, without or with cachexia (n = 26:24).

(B) Spearman correlation analysis of OTOP1 expression in scWAT and BMI in patients with cachexia (n = 24).

(C) Spearman correlation analysis of OTOP1 expression and BMI in individuals without cachexia (n = 26).

(D) OTOP1 expression in scWAT of patients with cancer with normal (n = 41) or low Alb (n = 9). Low Alb was defined as < 35 g/L.

(E) OTOP1 expression in patients with cancer with normal (n = 24) versus low Hb levels (Hb < 120 g/L; n = 26).

(F) OTOP1 expression in patients with cancer with normal (n = 27) versus abnormal CRP levels (CRP > 10 mg/L, n = 15). Data are presented as means ± SEM. Statistical significance was determined using an unpaired two-sided Student’s t test for normally distributed data and a two-sided Mann-Whitney U test for non-normally distributed data. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001. scWAT, subcutaneous white adipose tissue; Alb, abnormal albumin; Hb, hemoglobin; CRP, C-reactive protein.

Additionally, given the ongoing debate regarding the criteria for weight loss in cachexia,^3,38 we divided patients into two groups based on the median OTOP1 expression level: high expression and low expression. The results showed that patients with higher OTOP1 expression exhibited higher BMI and better Alb and Hb levels (Figure S6).

In conclusion, higher OTOP1 levels in scWAT are closely associated with the maintenance of BMI, Alb, and Hb levels in patients with cancer. These observations prompted us to further investigate the functional role of OTOP1 in adipocytes.

OTOP1 attenuates cachexia-induced metabolic dysfunction in adipocytes, partly dependent on PPARγ signaling

To investigate the role of OTOP1 in adipocytes under cachexia conditions, we employed an in vitro cachexia model using tumor-conditioned medium. As shown in Figure 6A, SVFs isolated from iWAT were induced to differentiate into mature white adipocytes. Treatment with LLC-conditioned medium resulted in increased expression of inflammation-related genes, decreased expression of key adipogenic transcription factors and lipogenesis-related genes, and increased expression of lipolysis-related genes (Figures 6C–6F). Overexpression of OTOP1 (Figure 6B) significantly reversed these changes, as evidenced by increased expression of adipogenesis and lipogenesis-related genes and reduced expression of lipolysis and inflammation-related genes, thereby improving lipid metabolic alterations (Figures 6C–6F). Moreover, OTOP1 overexpression also mitigated the reduction in lipid droplet formation induced by LLC-conditioned medium (Figure 6G).

Figure 6.

OTOP1 alleviates LLC-induced adipocyte metabolic dysfunction, partly dependent on PPARγ signaling

(A) Schematic representation of the differentiation of SVF-derived white adipocytes from iWAT, including treatment with LLC-conditioned medium and OTOP1 overexpression. Briefly, after 6 days of induction and differentiation, LLC-conditioned medium or control medium was added on day 6, together with control adenovirus or OTOP1-overexpression adenovirus. Cells were harvested on day 8.

(B–F) mRNA expression levels of Otop1 (B), adipogenesis-related genes (C), lipolysis-related genes (D), lipogenesis-related genes (E), and inflammation-related genes (F) in mature white adipocytes treated with LLC-conditioned medium or control medium, followed by OTOP1 overexpression or empty vector treatment (n = 4).

(G) Bright-field microscopy images showing lipid droplet formation in SVF-derived white adipocytes under different treatments (scale bars: 500 μm).

(H) Western blot analysis of phosphorylated NF-κB (pNF-κB-p65), total NF-κB-p65, and PPARγ protein levels in cells treated with LLC-conditioned medium or control medium, with or without OTOP1 overexpression.

(I) mRNA expression levels of Otop1 in mature white adipocytes treated with LLC-conditioned medium or control medium, with OTOP1 overexpression in the presence or absence of GW9662 (n = 5).

(J–M) mRNA expression levels of adipogenesis-related genes (J), lipolysis-related genes (K), lipogenesis-related genes (L), and inflammation-related genes (M) in adipocytes treated with LLC-conditioned medium or control medium, with OTOP1 overexpression in the presence or absence of GW9662 (n = 4–5).

(N) Western blot analysis of phosphorylated NF-κB p65, total NF-κB p65, and PPARγ protein levels in adipocytes treated with LLC-conditioned medium or control medium, with OTOP1 overexpression in the presence or absence of GW9662. Data are presented as mean ± SEM. Statistical significance was determined using one-way ANOVA followed by Tukey’s post hoc test for comparisons with equal variances. When variances were unequal, Welch’s ANOVA was used. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001. EV, empty adenoviral vector; Otop1^OE, OTOP1-overexpressing adenovirus; LLC, Lewis lung carcinoma-conditioned medium; DMEM, standard culture medium.

Systemic inflammation is a hallmark of cancer cachexia, and previous studies suggest that WAT plays a critical role in sustaining systemic inflammation during this condition.³⁹ Our results showed that the NF-κB signaling pathway was significantly enriched during cachexia (Figure 3E), with GSEA analysis identifying it as the most enriched inflammatory signaling pathway among the top 10 upregulated pathways (Figure 3F). We therefore further evaluated the regulatory effect of OTOP1 on NF-κB signaling. As expected, immunoblotting revealed that LLC-conditioned medium increased the levels of phospho-NFκB-p65. Notably, this upregulation significantly suppressed by OTOP1 overexpression (Figure 6H). Moreover, OTOP1 overexpression also effectively restored the protein levels of the key nuclear transcription factor PPARγ, which were reduced by LLC-conditioned medium (Figure 6H).

To further evaluate the potential involvement of PPARγ in the effects of OTOP1, adipocytes were treated with the PPARγ antagonist GW9662.⁴⁰ GW9662 treatment markedly attenuated the effects of OTOP1 overexpression on adipogenesis, lipogenesis, lipolysis, and inflammation-related gene expression (Figures 6J–6M). Meanwhile, the inhibitory effect of OTOP1 on NF-κB p65 phosphorylation was partially reversed (Figure 6N), suggesting that PPARγ signaling may be implicated in OTOP1-mediated regulation of adipocyte metabolism.

Local OTOP1 overexpression in adipose tissue alleviates cachexia-associated adipose loss

To evaluate the effect of OTOP1 on cachexia-associated adipose loss in vivo, Ad-OTOP1 (Otop1^OE) was locally delivered into the iWAT depot of LLC tumor-bearing mice. Compared with the control group, tumor-bearing mice exhibited a significant reduction in carcass body weight. OTOP1 injection attenuated body weight loss, and the body weight of OTOP1 treated mice was not significantly different from that of the control group (Figure 7A). Notably, OTOP1 injection did not alter tumor weight, suggesting that the protective effect of OTOP1 on adipose tissue was not attributable to changes in tumor growth (Figure 7B). Tissue weighting showed that OTOP1 significantly alleviated the reduction of both iWAT and eWAT in tumor-bearing mice (Figure 7C). Consistently, OTOP1 injection partially restored the reduction in adipocyte lipid droplet size in iWAT induced by cachexia (Figure 7D).

Figure 7.

Local OTOP1 overexpression in adipose tissue alleviates cachexia-associated adipose loss in vivo

Mice were divided into three groups: control mice without tumors (PBS), LLC tumor-bearing mice injected with empty vector (LLC+EV), and LLC tumor-bearing mice injected with Otop1-overexpressing vector (LLC+Otop1^OE) (n = 5:5:6).

(A) Carcass body weight of mice in the indicated groups.

(B) Tumor weight of mice in the LLC + EV and LLC + Otop1^OE groups.

(C) Tissue weights of iWAT and eWAT from mice in the indicated groups.

(D) Representative H&E staining images of iWAT from mice in the indicated groups (scale bars: 50 μm).

(E) mRNA expression levels of Otop1, adipogenesis-related genes, inflammation-related genes, lipolysis-related genes, and lipogenesis-related genes in iWAT from mice in the indicated groups.

(F) Western blot analysis of phosphorylated NF-κB p65, total NF-κB p65, and PPARγ protein levels in iWAT from mice in the indicated groups. Data are presented as mean ± SEM. Statistical significance was determined using one-way ANOVA followed by Tukey’s post hoc test for comparisons with equal variances. When variances were unequal, Welch’s ANOVA was used. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Further RT-qPCR analysis of iWAT demonstrated that Otop1 expression was significantly increased in the OTOP1-injected group. Compared with tumor-bearing mice, OTOP1 injection increased the expression of adipogenesis- and lipogenesis-related genes, while reducing the expression of lipolysis- and inflammation-related genes (Figure 7E). Consistently, OTOP1 injection markedly reduced the phosphorylation level of NF-κB p65 and restored PPARγ protein expression (Figure 7F).

Together, these results support a role for OTOP1 overexpression in adipose tissue in attenuating cancer cachexia-associated adipose loss and improving adipose metabolic dysfunction in vivo.

Discussion

In the present study, our findings suggest that OTOP1 contributes to adipose tissue remodeling during cancer cachexia. Through transcriptomic analysis of iWAT from mouse models representing both the pre-cachexia and cachexia stages, we observed that Otop1 expression exhibited dynamic changes during disease progression. In patients with cancer, lower OTOP1 expression in scWAT was associated with reduced BMI and nutritional indicators. Functional experiments suggested that OTOP1 may suppress NF-κB signaling and activate PPARγ, thereby contributing to reduced lipolysis and maintenance of adipose homeostasis. Furthermore, in vivo overexpression of OTOP1 in adipose tissue partially rescued adipose tissue loss in tumor-bearing mice. Together, these findings suggest that OTOP1 plays an important role in regulating adipose tissue metabolism during cancer cachexia.

Previous studies have identified multiple regulatory factors involved in adipose tissue wasting during cachexia, many of which originate from tumors or the inflammatory microenvironment.² Inflammatory cytokines such as IL-6 and TNF-α promote lipolysis through activation of inflammatory signaling pathways and are associated with elevated circulating free fatty acids (FFAs).²² However, clinical interventions targeting TNF-α or IL-6 signaling have shown limited therapeutic efficacy.⁶ In recent years, GDF15 has been recognized as an important mediator of cachexia.^41,42 Circulating levels of GDF15 are elevated in multiple cancers,⁴¹ and implantation of tumor cells producing GDF15 in mice can enhance lipolytic metabolism.¹⁴ The identification of the GDF15 receptor further clarified its role in regulating the anorexia-cachexia syndrome.^14,43 Currently, a humanized selective monoclonal antibody targeting GDF15 has entered phase clinical trials.⁴⁴ Despite these advances, most studies have focused on how tumor-derived or inflammation-derived signals drive adipose tissue wasting, whereas the intrinsic regulatory mechanisms within adipose tissue remain relatively underexplored. Our findings suggest that OTOP1 may serve as an intrinsic adipose tissue factor involved in adipose tissue remodeling, potentially contributing to protection against adipose tissue depletion.

OTOP1 is a member of the otopetrin protein family and is localized to the plasma membrane. The family also includes OTOP2 and OTOP3,⁴⁵ all of which are proton-selective ion channels.²⁸ OTOP1 mediates proton (H⁺) transport across the cell membrane and thereby participates in the regulation of intracellular pH homeostasis.⁴⁶ OTOP1 is highly expressed in type III taste receptor cells and plays an essential role in sour taste perception.⁴⁷ However, its function in WAT remains largely unknown. A limited number of studies suggest that OTOP1 may participate in obesity-associated adipose tissue inflammation.^31,32 In addition, OTOP2 has been reported to suppress proliferation and migration of colorectal cancer cells,⁴⁸ whereas OTOP3 has been shown to inhibit ferroptosis and promote colorectal cancer progression.⁴⁹ These findings suggest that the OTOP family may play broader roles in metabolic regulation and tumor-related diseases that warrant further investigation.

During the pre-cachexia phase of cancer, adipose tissue exhibits early signs of inflammatory responses and metabolic adaptations, accompanied by a marked upregulation of UCP1. Previous studies have shown that in the early stages of cancer cachexia, WAT tends to undergo browning toward a beige-like phenotype, accompanied by increased UCP1 expression.⁵⁰ This browning process is mediated by multiple inflammatory factors. However, our data indicate that UCP1 expression is significantly elevated only during the pre-cachexia phase, with no notable changes observed in the cachexia phase. Similarly, clinical studies have reported that UCP1 expression in WAT is not increased in patients with gastrointestinal cancer-associated cachexia compared with healthy controls.⁵¹ Therefore, these findings suggest that the upregulation of UCP1 in the pre-cachexia phase may represent a transient adaptive response rather than a major contributor to sustained adipose tissue wasting. However, as mice were housed under standard laboratory conditions (22°C) rather than thermoneutral conditions (30°C), we cannot exclude the possibility that standard laboratory temperature may have amplified the observed transient increase in UCP1 expression.

As cancer progresses to the cachexia phase, adipose tissue loss coincides with transcriptional reprogramming of protein metabolism and elevated inflammatory signaling. Our transcriptomic analysis showed that the PPAR signaling pathway is significantly upregulated in the pre-cachexia stage but markedly reduced in the cachexia phase, accompanied by decreased Pparγ mRNA expression. PPARγ is highly expressed in adipose tissue, where its activation exerts anti-inflammatory effects, partly through inhibition of NF-κB signaling.^52,53 Previous studies have demonstrated that NF-κB activation can suppress PPARγ expression.⁵⁴ Consistent with these observations, our in vitro experiments further showed that OTOP1 overexpression was accompanied by reduced NF-κB signaling and increased PPARγ expression. In parallel, transcriptional analysis indicate elevated NF-κB signaling at the transcriptional level during cachexia. Previous studies have reported that NF-κB activation plays a central role in regulating pro-inflammatory cytokine expression, inducing the transcription of cachexia-associated mediators such as IL-6, TNF-α, and various chemokines.⁵⁵ Therefore, NF-κB signaling could represent a potential therapeutic target in the context of cancer cachexia.

Previous transcriptomic studies have explored molecular changes in adipose tissue during cancer cachexia.^56,57,58 However, most of these studies have focused on late-stage cachexia or a single time point, and the identified molecular alterations may represent secondary responses to disease progression. In contrast, our study identified candidate factors from the perspective of disease progression. These early molecular changes more closely align with adipose tissue remodeling, supporting the identification of OTOP1 as a candidate factor associated with cachexia-related adipose tissue remodeling. Currently, the staging of cachexia largely relies on clinical manifestations, such as anorexia and weight loss, as well as biochemical markers including CRP, Hb, and Alb.⁵⁹ However, these indicators often reflect metabolic disturbances only after they have already occurred. In addition, factors such as ascites, edema, and population heterogeneity may compromise assessments based on body weight or BMI.^8,60 Previous studies have suggested that cachexia may remain reversible when interventions are initiated during the pre-cachexia stages.⁶¹ In the patient cohort analyzed in this study, several individuals exhibited decreased OTOP1 expression along with reduced Alb or Hb levels, despite maintaining stable body weight or a normal BMI, indicating a potential risk of cachexia development. Together with our in vivo and in vitro findings, these observations suggest that OTOP1 may participate in early metabolic alterations during the development of cancer cachexia.

In conclusion, this study systematically characterized transcriptomic alterations in WAT during cancer cachexia progression and identified OTOP1 as a candidate factor related to lipid metabolism. Reduced OTOP1 expression was closely associated with malnutrition in patients with cancer cachexia, while OTOP1 overexpression alleviated adipose tissue wasting, accompanied by modulating of inflammation and lipid metabolism, partly dependent on NF-κB/PPARγ signaling. These findings provide new insights into adipose tissue alterations during cachexia and support the potential of targeting adipose metabolism for therapeutic intervention.

Limitations of the study

This study has several limitations. First, the protective role of OTOP1 was mainly examined using overexpression approaches. Adipocyte-specific Otop1 knockout models will be required to determine whether OTOP1 is essential for maintaining adipose tissue homeostasis during cancer cachexia. Second, although our findings suggest that OTOP1 may influence adipose tissue metabolism partly through NF-κB/PPARγ signaling, the precise molecular mechanisms remain to be fully elucidated. In particular, direct genetic manipulation of Pparγ would be valuable to more precisely determine its role in mediating the effects of OTOP1. Third, the mechanisms by which OTOP1 regulates intracellular metabolic processes remain incompletely understood, particularly regarding how its proton channel activity may influence cellular bioenergetics and metabolic homeostasis. Finally, the number of clinical samples included in this study was relatively limited. In addition, potential variability associated with different anti-tumor treatment regimens among patients was not specifically considered in the current analysis. Future studies involving larger and more diverse patient cohorts, as well as longitudinal analyses, will be necessary to further validate the expression characteristics of OTOP1 and to clarify its dynamic changes during cancer progression.

Resource availability

Lead contact

Requests for further information and resources should be directed to and will be fulfilled by the lead contact, Na Chen (chenna@wmu.edu.cn).

Materials availability

This study did not generate new unique reagents.

Data and code availability

This paper does not report original code. Sequencing data generated in this study have been deposited in the Gene Expression Omnibus (GEO) under accession number GSE317738 and are publicly available. All other data supporting the findings of this study are available from the lead contact upon reasonable request.

Acknowledgments

This study was supported by grants from National Key Research and Development Program of China (2023YFC2506000 and 2023YFC2506001), National Natural Science Foundation of China (82400989, 82470886, and 82501073), and the Natural Science Foundation of Zhejiang Province (LQ24H070008).

Author contributions

D.L.: conceptualization, investigation, methodology, and writing – original draft; X.Y.: investigation, data curation, formal analysis, and methodology; W.Z.: investigation and data curation; C.H.: investigation and formal analysis; Z.L.: investigation and visualization; J.W.: conceptualization and writing – review and editing; D.H.: resources and validation; W.G.: funding acquisition, project administration, and writing – review and editing; X.S.: conceptualization, project administration, resources, and supervision; N.C.: conceptualization, supervision, funding acquisition, and writing – review and editing.

Declaration of interests

The authors declare no competing interests.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work, the authors used “ChatGPT” in order to improve readability and language. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
HSP90 (C45G5) Rabbit mAb	CST	Cat# 4877s, RRID: AB_2233307
anti-phospho-NF-κB p65	CST	Cat# 3033T, RRID: AB_331284
anti-NFκB p65, C-20	Santa Cruz	Cat# Sc-372, RRID: AB_632037
anti-PPARγ	Santa Cruz	Cat# Sc-7273, RRID: AB_628115
anti-UCP1	Abcam	Cat# ab10983, RRID: AB_2241462
anti-Perilipin 1	CST	Cat# 9349s, RRID: AB_10829911
Anti-rabbit IgG, HRP-linked Antibody	CST	Cat# 7074, RRID: AB_2099233
Anti-mouse IgG, HRP-linked Antibody	CST	Cat# 7076, RRID: AB_330924
Bacterial and virus strains
Ad-Otop1	GeneChem	N/A
Ad-EGFP	GeneChem	N/A
Chemicals, peptides, and recombinant proteins
1 × Phosphate-Buffered Saline	Meilunbio	Cat# MA0015
Trypsin-EDTA (0.05%)	Gibco	Cat# 25300062
DMEM/F12	Gibco	Cat# 11320082
Fetal bovine serum	Gibco	Cat# 12484028
L-Glutamine	Gibco	Cat# 25030-081
Penicillin-streptomycin solution	Gibco	Cat# 15140122
Insulin	Novo Nordisk	N/A
3-isobutyl-1-methylxanthine	Sigma	Cat# I7018
Dexamethasone	Sigma	Cat# D4902
Rosiglitazone	Sigma	Cat# R2408
Collagenase from Clostridium histolyticum type II	Sigma	Cat# C6885
HEPES (1M)	Gibco	Cat# 15630080
Lipofectamine™ 2000 Transfection Reagent	Invitrogen	Cat# 11668019
4% Paraformaldehyde Fix Solution	Servicebio	Cat# G1101
DAPI Fluoromount-G®	Beyotime	Cat# P0131
RIPA lysis buffer	Shanghai Biocolors	Cat# R20095
Halt™ Protease and Phosphatase Inhibitor Cocktail (100∗)	Thermo Fisher Scientific	Cat# 78444
Protein Sample Loading Buffer	Yamei	Cat# LT103
Bovine serum albumin (BSA)	GBCBIO	Cat# 0332
Western Lightning Plus, Chemiluminescent Substrate	PerkinElmer	Cat# NEL104001EA
PrimeScript RT Master Mix (Perfect Real Time)	Takara	Cat# RR036
ChamQ Universal SYBR qPCR Master Mix	Vazyme	Cat# Q711
GW9662 (PPARγ antagonist)	MCE	Cat# HY-16578
Critical commercial assays
Pierce™ BCA Protein Assay Kits	Thermo Fisher Scientific	Cat# 23227
Super Total RNA Extraction Kit	Promega	Cat# LS1040
NEBNext Ultra RNA Library Prep Kit for Illumina	New England Biolabs	Cat# NEB7530
Deposited data
Mouse iWAT RNA-seq data generated in this study	Gene Expression Omnibus	GEO: GSE317738
Experimental models: Organisms/strains
Human subcutaneous white adipose tissue	The First Affiliated Hospital of Wenzhou Medical University	N/A
SPF C57BL/6J male mice	Shanghai Jihui Laboratory Animal Care Co.,Ltd	N/A
Lewis lung carcinoma cells	ATCC	Cat# CRL-1642
HEK293 cells	ATCC	Cat# CRL-1573
Mouse primary stromal vascular fraction cells	This paper	N/A
Oligonucleotides
Primers for qPCR, see Table S2	This paper	N/A
Software and algorithms
GraphPad Prism (version 9.0)	GraphPad	http://www.graphpad.com/scientific-software/prism/
Adobe Illustrator 2022	Adobe	https://www.adobe.com/
SAS v8.0	SAS Institute	N/A
Other
PVDF membranes	Bio-rad	Cat# 1620177
40 μm strainer	FALCON	Cat# 352340
Comprehensive Laboratory Animal Monitoring System	Columbus Instruments	N/A
QuantStudio Dx Real-Time PCR Instrument	Thermo Fisher Scientific	N/A
NanoDrop ND2000 spectrophotometer	Thermo Fisher Scientific	N/A
Illumina NovaSeq 6000 System	Illumina	N/A
TissueFAXS Plus	TissueGnostics GmbH, Austria	N/A
ImageQuant LAS 4000	GE Healthcare	N/A

Experimental model and study participant details

Human subcutaneous white adipose tissue samples

Patients were selected from Colorectal Anal Surgery and Department of Gastrointestinal Surgery, The First Affiliated Hospital of Wenzhou Medical University between November 2023 and November 2025. Participants were excluded for heart failure, hepatic or renal dysfunction, uncontrolled diabetes mellitus, AIDS, active or uncontrolled infection, or the use of anabolic or investigational agents. scWAT samples were obtained from subcutaneous fat near the surgical incision site during tumor resection surgeries. The study was approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University (Approval No.: KY2022-202). All participants provided written informed consent prior to inclusion in the study, and the privacy rights of human subjects were fully respected. Participants demographic and clinical characteristics are provided in Table S1.

Animals

C57BL/6J mice were acquired from Shanghai Jihui Experimental Animal Care Co., Ltd. For the LLC tumor-bearing mouse model, 8- to 10-week-old male mice were used. For the isolation of stromal vascular fraction (SVF) cells, 4-week-old male mice were used. Mice were housed in standard cages within a specified pathogen-free (SPF) facility, maintained on a 12-h light/dark cycle (07:00–19:00) at 22 °C, with ad libitum access to food and water.

The sample size was established via preparatory tests, requiring a minimum of four mice per group to provide sufficient statistical power. For tumor-bearing experiments, mice were randomly allocated to control (Day 7-PBS or Day 21-PBS) or experimental (Day 7-LLC or Day 21-LLC) groups based on comparable average body weights. Mice were housed separately during tumor implantation. All animal procedures were conducted in accordance with the ARRIVE guidelines and were approved by the Animal Care and Use Committee at Wenzhou Medical University (Approval No.: 2024-137).

Cell lines and primary adipocytes

LLC cells were cultured in DMEM supplemented with 10% FBS, 1% penicillin-streptomycin, and 1 mM L-glutamine at 37 °C in a humidified atmosphere containing 5% CO₂. LLC cells were used for subcutaneous tumor implantation in mice and for the preparation of conditioned medium.

Primary white adipocytes were differentiated from stromal vascular fraction (SVF) cells isolated from inguinal white adipose tissue of 4-week-old C57BL/6J mice. SVF cells were initially cultured in DMEM/F12 supplemented with 10% FBS, 1% penicillin-streptomycin, and 1 mM L-glutamine at 37 °C in a humidified atmosphere containing 7.5% CO₂ until confluence reached 100%. Differentiation was induced during the first 2 days with a mixture containing 8.4 μg/mL insulin (Novo Nordisk), 1 μM dexamethasone, 1 μM rosiglitazone, and 0.5 mM 3-isobutyl-1-methylxanthine (all from Sigma-Aldrich). Cells were then maintained in adipocyte medium containing insulin. On day 6 of differentiation, primary adipocytes were used for adenoviral transduction and conditioned medium treatment. Detailed procedures for adenoviral transduction and pharmacological treatment are provided in the method details section.

Method details

LLC tumor-bearing mouse model

To ensure accurate cell counting before tumor implantation, LLC cells were digested, resuspended, and equally divided into five Eppendorf tubes for counting. Experimental groups were distinctly identified to prevent errors, and no blinding was employed. LLC cells (5 × 10⁶ per mouse) were administered subcutaneously into the flank of the mice, whereas control mice received PBS injections.²³ Mice in the pre-cachexia condition were euthanized 7 days post-injection of LLC cells or PBS^7,62; mice in the cachexia condition were euthanized 21 days after injection.²³

In situ adenoviral injection in iWAT

To evaluate the role of OTOP1 in vivo, in situ adenoviral injection was performed in the iWAT of LLC tumor-bearing mice. Mice were anesthetized with isoflurane, and Ad-Otop1 or Ad-EGFP was injected into the iWAT at day 8 after tumor inoculation using a multi-site injection approach. A viral dose of 1 × 10⁹ PFU per side was administered. Mice were euthanized 7 days after injection, and tissues were collected for subsequent analyses.

Whole-body metabolic measurements

Whole-body metabolic measurements were performed using a Comprehensive Laboratory Animal Monitoring System (CLAMS, Columbus Instruments, USA). Mice were housed individually and acclimated to the system for 24 h prior to data collection. Oxygen consumption (VO₂), carbon dioxide production (VCO₂), and spontaneous locomotor activity were continuously monitored for 24 h. The respiratory exchange ratio (RER) was calculated as the ratio of VCO₂ to VO₂.

Morphological and immunofluorescence analysis

iWAT was collected from the contralateral (non-tumor-injected) side, fixed in 4% paraformaldehyde, and embedded in paraffin. Sections of 5 μm thickness were prepared and stained with hematoxylin and eosin (H&E) according to standard protocols. For immunofluorescence, a tyramide signal amplification approach was utilized. Paraffin sections of iWAT were incubated with UCP1 antibody (ab10983, Abcam; 1:500 dilution) and perilipin antibody (9349s, CST; 1:200 dilution). Tyramide-488 and tyramide-594 were used for signal amplification, and antigen retrieval was performed using 1 mM Tris-EDTA buffer (pH 9.0, Sigma). Slides were mounted with an anti-fade medium that included DAPI (P0131, Beyotime). Full-slide scans were obtained using an automated system (TissueFAXS Plus, TissueGnostics). Representative images were obtained from at least three mice per group.

Adenovirus preparation

Mouse Otop1 (RefSeq: NM_172709.3) was amplified from the cDNA library of Genechem (Shanghai, China) with the following primers: forward: 5′-AGGTCGACTCTAGAGGATCCCGCCACCATGCCTGGGGGCC-3′ and reverse: 5′-TCCTTGTAGTCCATACCGGTGATCTTACAATAGACCTCAAAG-3′. The adenovirus vector plasmid GV314 (CMV-OTOP1-3FLAG-SV40-EGFP) was used. The vector and Otop1 gene sequence were digested by BamHI and AgeI restriction enzymes, and complete cloning through In-fusion recombination method. Recombinant vector was detected by DNA sequencing. The shuttle plasmid was recombined with pBHGlox_ΔE1,3Cre plasmid (Microbix) in HEK293A cells. After extensive cytopathic effect was observed, the virus was harvested from HEK293A cells using three freeze-thaw cycles, Plaque purification was amplified by serial infection, followed by purification using an Adeno-X Virus Purification Kit (Takara). The adenovirus titer in plaque-forming units (PFU) was determined by a plaque formation assay in HEK293 cells. The resulting adenovirus was referred to as Ad-Otop1, and the empty EGFP-expressing adenovirus was used as the Ad-EGFP control.

LLC-conditioned medium preparation

LLC cells were then seeded and cultured until approximately 80% confluency, at which point the medium was refreshed. LLC-conditioned medium was collected 24 h later when cells reached full confluency.

For adipocyte treatment, the LLC-conditioned medium treatment consisted of 50% fresh DMEM/F12 medium (containing 10% FBS, 1% penicillin-streptomycin, and 1 mM L-glutamine) and 50% LLC cell-conditioned medium. The control medium consisted of 50% fresh DMEM/F12 medium and 50% complete DMEM supplemented with 10% FBS, 1% penicillin-streptomycin, and 1 mM L-glutamine.

Isolation, differentiation and treatment of primary white adipocytes

The stromal vascular fraction (SVF) were isolated from iWAT of 4-week-old male C57BL/6J mice and subsequently induced to differentiate into mature white adipocytes. Briefly, iWAT was dissected, minced, and digested with type II collagenase (C6885, Sigma) at 37 °C for 30–40 min, with the reaction quenched with DMEM containing 10% FBS. The suspension was filtered through a 40 μm filter (Falcon) and transferred into 6-cm culture dishes.

On day 6 of differentiation, primary adipocytes were transduced with Ad-Otop1 or Ad-EGFP at a multiplicity of infection (MOI) of 25. An empty adenoviral vector expressing EGFP was used as a control to balance the final viral load. After 12 h of transduction, the medium was replaced with fresh culture medium. Cells were then treated with either LLC-conditioned medium or control medium for 36 h.

For pharmacological inhibition of PPARγ experiments, cells were treated with the PPARγ antagonist GW9662 (20 μM) for 24 h. Cells were harvested on day 8 of differentiation for subsequent analyses.

RNA extraction and real-time PCR analysis

Total RNA was extracted from cultured cells or frozen adipose tissue using the Eastep Super Total RNA Extraction Kit (ls1040, Promega). RNA concentration and the purity (A260/280) were measured using a NanoDrop ND2000 spectrophotometer (Thermo Scientific). Reverse transcription was performed with the PrimeScript Reverse Transcript Master Mix (RR036A, TaKaRa). Quantitative PCR was conducted on a QuantStudio Dx Real-Time PCR System (Thermo Fisher Scientific). Relative mRNA expression levels were calculated using the comparative 2-ΔΔCT method, with 36B4 or Actb used as internal reference genes.

Protein preparation and western blot analysis

Total protein was extracted using RIPA lysis buffer (R20095, Biocolors) with a phosphatase inhibitor mixture (78444, Thermo Fisher Scientific). Proteins were denatured in boiled water, separated by 7.5% or 10% SDS-PAGE, and transferred to a PVDF membrane (Bio-Rad). After blocking, the membrane was incubated overnight at 4 °C with primary antibodies. Bands were visualized using a chemiluminescent imaging analyzer (GE, ImageQuant LAS4000). All protein samples were quantified and analyzed by immunoblotting with the indicated antibodies. HSP90 (4877s, CST, 1:1,000 dilution) was used as an internal control, along with the following primary antibodies: anti-phospho-NF-κB p65 (CST, 3033T), anti-NF-κB p65 (C-20) (Santa Cruz, Sc-372), anti-PPARγ (Santa Cruz, Sc-7273), anti-UCP1 (Abcam, ab10983).

RNA sequencing and bioinformatic analysis

After total RNA was extracted from mouse iWAT and quality assessed, eukaryotic mRNA was enriched by Oligo (dT) beads. Then the enriched mRNA was fragmented into short fragments using fragmentation buffer and reversely transcribed into cDNA by using NEBNext Ultra RNA Library Prep Kit for Illumina (NEB #7530, New England Biolabs, Ipswich, MA, USA). The purified double-stranded cDNA fragments were end repaired, A base added and ligated to Illumina sequencing adapters. The ligation reaction was purified with the AMPure XP Beads (1.0X). And polymerase chain reaction (PCR) amplified. The resulting cDNA library was sequenced using Illumina Novaseq6000 by Gene Denovo Biotechnology Co. (Guangzhou, China). Reads containing adapters and low-quality reads were removed by fastp (v. 0.23.0). For each transcription region, an FPKM (fragment per kilobase of transcript per million mapped reads) value was calculated to quantify its expression abundance and variations, using RSEM software. Genes with adjusted p value (FDR) < 0.05 and absolute fold change ≥1.5 were considered to be significantly differentially expressed genes between the two samples. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) regulatory pathways were plotted using the OmicShare tools at https://www.omicshare.com/tools.

Quantification and statistical analysis

Data are presented as mean ± s.e.m. unless otherwise indicated. The Shapiro-Wilk test was used to assess the normality of data distribution to determine the appropriate analytical approach. For normally distributed data, differences between two groups were analyzed using Student’s t test (for equal variances) or Welch’s t test (for unequal variances). For non-normally distributed data, the Mann-Whitney U test was applied. For analyses involving multiple groups, One-Way ANOVA was performed, followed by Tukey’s post hoc tests when equal variances were assumed, or Welch’s ANOVA when variances were unequal. Correlation analyses were performed using Spearman correlation tests. Statistical significance was defined as p < 0.05. Exact n values, statistical tests, and definitions of statistical significance are provided in the corresponding figure legends. Statistical analyses were conducted using GraphPad Prism v9 (GraphPad Software) and SAS v8.0 (SAS Institute).