Cachectic patients with gastric cancerwho underwentsurgery in Zhongshan Hospital of Fudan University from 2018.06 to 2020.06 were includedin this study. Inclusive criteria for the study were: (1) patients diagnosed with gastric adenocarcinomacancer (not gastric stromal tumor orlymphoma); (2) patients received surgical treatmentwithout preoperative radiotherapy or chemotherapy; (3) patients with abdominal CT examinations and complete clinical data; (4) patients with weight loss >5% in recent 6 months before surgery. This study was approved by the Ethics Committee of Zhongshan Hospital of Fudan University (B2019-193R). Written informed consents were obtained from all patients.
Clinical data collection
Height, weight, gender, and age were extracted from the preoperative medical records. Body mass index (BMI) was calculated as body weight (kg)/height2 (m2).Cachexia-related indicators were extracted from preoperative blood biochemical examinations. Areas of SAT and VAT from CT scans at the third lumbar vertebra were measuredas described before.
Human tissue specimens
Adipose tissues were obtained from enrolled patients. At the beginning of the operation, about 500 mg of subcutaneous adipose tissue near the median abdominal incision was obtained. About 500 mg of omental adipose tissue was taken as visceral adipose tissue within 30 minutes after gastric cancer specimens were isolated. The adipose tissue was immediately stored in liquid nitrogen at -80 ℃ or transferred into tissue fixative for further analysis.
Mouse model of cancer cachexia
The mouse model of cancer cachexia refers to the previous methods. In brief, Cachectic mice were induced by subcutaneous injection of colon-26 adenocarcinoma cells into the right flank of the mice. The littermate control mice received PBS injection only. Micewere euthanized at day 21 post-injection and were dissected toharvestinguinal white adipose tissue (SAT) and epididymal white adipose tissue (VAT). Weight of SAT and VAT was recorded at day 0 (control mice) and day 21 (cachectic mice). The proportion of adipose tissues loss was calculated by weight change (weight at day 0subtract weight at day 21) divided to initial weight. Allanimal studies were performed in accordance with the guidelinesprovided by Animal Care Committee of Fudan University.
The total RNA was extracted from 3 paired SAT and VAT from gastric cancer patients with cachexia. After quantification and qualification,a total amount of 1 μg RNA per sample was used as input material for the RNAsample preparations. Sequencing libraries were generated using NEBNextUltraTM RNA Library Prep Kit for Illumina (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumina, USA) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Novaseq platform and 150bp paired-end reads were generated. FeatureCounts v1.5.0-p3 was used to count the reads numbers mapped to each gene. Fragments per kilobase million (FPKM) of each gene was calculated based on the length of the gene and reads count mapped to this gene. The raw sequencing dataset that supported the resultsof this study was deposited in the NCBI GEO database. The data areaccessible through GEO: GSE186466.
RNA sequencing data analysis
Differential expression analysis of twogroupswas performed using theDESeq2 R package. Differentially expressed transcripts between the two groups were identified when |logFoldChange| >0and the p value <0.05. Gene Ontology (GO) enrichment analysis of DEGs wasimplemented by the ClusterProfiler R package, in which gene length biaswascorrected. We also used ClusterProfiler R package to test thestatistical enrichment of differential expression genes in KEGG pathways. GO terms and KEGG pathways with corrected p value <0.05 were consideredsignificantly enriched by differential expressed genes.
Conventional enrichment analysis based on hypergeometric distribution depends on significantly up-regulated or down-regulated genes, and it is easy to omit some genes with insignificant differential expression but important biological significance. Gene set enrichment analysis (GSEA) does not need to specify a clear differential gene threshold. All genes are sorted according to the degree of differential expression in the two groups of samples, and then statistical methods are used to test whether the preset gene set is enriched at the top or low section of the sorting table. GSEA mainly includes three steps: calculation of enrichment score; estimation of the significance level of enrichment score; multiple hypothesis tests.
The PPI network of DEGs was predicted using the Search Tool for the Retrieval of Interacting Genes (STRING) database. The interaction score threshold of 0.4 was set as the cut-off criterion. The PPI network was constructed using Cytoscape. Comprehensive experimentally validated miRNA-gene interaction data were collected from TargetBase. Transcription factor and gene target data derived from the ENCODE ChIP-seq data. Only peak intensity signal <500 and the predicted regulatory potential score <1 is used (using BETA Minus algorithm).
Cell culture and differentiation
The mouse immortalized white preadipocytes werekindly provided by Professor Qiurong Ding from the Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences. Thiscell line has been described previously and used in several studies toassess the effects of different factors on adipose differentiation andfunction. The culture and differentiation methods of preadipocytes cell lines were as previously reported.
Plasmid and siRNA construction
The IRX1 expression plasmid pcDNA3.1þ/IRX1 and empty plasmid pcDNA3.1þ were designed and synthesized by GenePharma (Shanghai, China). Small interfering RNAs (siRNAs) targeting IRX1 were also designed by GenePharma. Cell transfection was conducted using Lipofectamine RNAiMAX Transfection Reagent kit (Invitrogen,USA) or Lipofectamine 2000 Transfection Reagent (Invitrogen, USA) according to the manufacturer’s instruction
Hematoxylin-eosin and Immunohistochemical staining
All the samples were transferred totissue fixativeafter being harvested. The protocols were previously described. In brief, histological sections of adipose tissue were stained with hematoxylin–eosin to evaluate morphological changes and the adipocyte cross-sectional area (CSA). A total of 10 randomly selected fields for each sectionwere captured and analyzed to evaluate adipocyte CSA with a computerized imaging software (ImageJ, USA).For immunohistochemistry, the positive cellsin 10 randomly selected fields per section were counted and evaluated by two independent researchers. And the mean number of positive cells per field was calculated.
Oil Red O (ORO) staining
Mature adipocytes were fixed with 4% formaldehyde for 30 min, then washed twice with PBS. They were stained with 0.3% ORO solution and washed three times with distilled water. To assess lipid accumulation, the dye retained in the cells was dissolved in isopropanol and the absorbance of the resulting solution at 520 nm was examined.
RNA isolation and qRT-PCR
Total RNA was isolated from adipose tissues and adipocytes using TRIzol Reagent (Invitrogen, USA) according to the manufacturer’s recommendations.cDNA was synthesized from 1 μg total RNA using FastKing RT Kit (Tiangen, China).Gene expression analysis was performed using Prime-Script RT master mix (Takara, Japan) in StepOnePlusReal-Time system (Applied Biosystems, USA). Expression levels of targeted geneswerenormalized to the expression of GAPDH. qRT-PCR was performedaccording to the manufacturer’s instructions and the relativefold change was calculated by the 2-ΔΔCt method. Primers were designed and synthesized by Sangon Biotech (Shanghai, China) and are listed in Additional file: Table S2. All experiments were repeated at least three times.
Western blot analysis
Preparation of total protein lysates and western blot analysis were performed as previously described. Primary antibodiesagainst IRX1 (Immunoway,YT2412), CEBPα (Cell signaling technology, #2295),AdipoQ(Cell signaling technology, #2789), and FABP4(Cell signaling technology, #2120)were used. Tubulin expression wasused as an endogenous control.
Statistical analyses were performed using GraphPad Prism software. Data calculated from independent experiments were presented as the mean ±standard deviation and a student’s t-test was performed to compare the differences between two groups. To analyze the correlation between IRX1 mRNA levels in SAT and the clinicopathological factors in gastric cancer patients with cachexia, we divided 61 patients into two groups according to the IRX1expression in SATcompared to VAT. Comparisons between these two groups were made using thet-test for continuous data and χ2 test for categorical data.p<0.05 was considered statistically significant.