Osteosarcoma (OS) is the most common primary malignant bone tumor in adolescents and the elderly. It is highly aggressive and frequently metastasizes to the lungs. The introduction of multi-agent chemotherapy in the 1970s pushed 5-year survival rates from roughly 20% up to approximately 70%, but overall therapeutic progress has stalled over the past three decades. Identifying new molecular targets is therefore a pressing clinical need.
Fatty acid synthase (FASN) as a cancer driver: FASN is the central enzymatic system for de novo synthesis of long-chain fatty acids in mammalian cells. It consists of two identical multifunctional polypeptides that together catalyze a series of condensation, reduction, and dehydration reactions to convert acetyl-CoA and malonyl-CoA into palmitate. In normal adult tissue, FASN expression is low; in cancer cells, FASN is frequently overexpressed and functions as an oncogene, supporting membrane biosynthesis, post-translational lipid modifications, and anabolic growth. FASN overexpression has been documented as a prognostic biomarker in gastric adenocarcinoma and breast cancer. In osteosarcoma specifically, prior work by this research group showed that FASN promotes migration and invasion through PI3K/Akt signaling, but the broader protein-level changes downstream of FASN had not been mapped systematically.
The gap this paper fills: The authors used iTRAQ (isobaric tags for relative and absolute quantitation) proteomics, a quantitative mass spectrometry approach, to comprehensively profile which proteins change expression when FASN is silenced in osteosarcoma cells. This allowed them to generate an unbiased map of FASN's downstream protein network, identify biologically enriched pathways, and select the most clinically relevant candidate targets for follow-up validation.
The study was funded by the National Natural Science Foundation of China and conducted at the First Affiliated Hospital of Nanchang University. It combined cell biology, proteomics, bioinformatics, and clinical specimen analysis in 71 osteosarcoma patient samples, making it one of the more comprehensive single-institution studies of FASN function in this cancer type.
The study design integrated multiple methodological layers, moving from discovery proteomics through bioinformatic filtering to mechanistic in vitro and clinical validation. The osteosarcoma cell lines used were 143B and HOS, both authenticated by STR profiling and obtained from the Chinese Academy of Science. A normal human osteoblast cell line (hFOB1.19) was included as a non-malignant control. Stable FASN knockdown was achieved using lentiviral delivery of short hairpin RNA (shFASN), with cells selected under puromycin. A scrambled non-targeting shRNA (shNC) served as the control.
iTRAQ quantitative proteomics: Proteins from 10^7 143B cells per group (three parallel biological replicates each) were extracted using SDT buffer, digested with trypsin by the filter-aided sample preparation (FASP) method, and labeled with iTRAQ isobaric tags. Labeled peptides were fractionated by high-pH reversed-phase liquid chromatography and analyzed by LC-MS/MS on a Thermo Scientific instrument using nanometric flow. Spectra were processed with MASCOT (version 2.2) and Proteome Discoverer (version 1.4) against the SwissProt Human database, using a target-decoy strategy and a 1.2-fold change threshold with p less than or equal to 0.05 to define differentially expressed proteins (DEPs). Fragment mass tolerance was set at 0.1 Da and peptide mass tolerance at plus or minus 20 ppm.
Bioinformatics pipeline: GO (Gene Ontology) annotations were generated using Blast2GO (version 5.2.5). KEGG pathway enrichment analysis was performed with the KASS (KEGG Automatic Annotation Server) tool and Fisher's exact test. Protein-protein interaction (PPI) networks were built from the String database and visualized in Cytoscape (version 3.2.1). The R2 genomics analysis platform was used to query correlation and survival data across 127 publicly available mixed osteosarcoma samples. GEO dataset GSE99671 (18 OS and paired normal tissues) provided independent expression data. Kaplan-Meier survival analysis was applied to clinical specimens.
Functional assays in cells: HNRNPA1 was identified as the top candidate for further study, and its functional role was tested using CCK-8 proliferation assays, colony formation assays (8-day culture), wound-healing scratch assays (0 and 24 h time points), and Matrigel-based transwell migration and invasion assays in both 143B and HOS cells. IHC scoring in 71 patient tumor samples combined staining intensity (0-3 scale) and percentage of positive cells (0-4 scale), with scores ranging from 0 to 12.
Among the 4,971 proteins quantified by iTRAQ in FASN-silenced versus control 143B osteosarcoma cells, a total of 567 differentially expressed proteins (DEPs) met the 1.2-fold change and p less than or equal to 0.05 criteria. Of these, 325 were upregulated and 242 were downregulated following FASN silencing. The protein ratio distribution, volcano plots, and hierarchical heat maps confirmed the reproducibility and significance of the quantitative changes across the three biological replicate pairs.
Top upregulated proteins: The 10 most strongly upregulated DEPs in FASN-silenced cells were HIST1H2AB (histone H2A type 1-B/E, 3.23-fold), INA (alpha-internexin, 2.66-fold), INTS5 (integrator complex subunit 5, 2.44-fold), MTCH2, EIF1, MAPK1IP1L, PXK, RPS27, PM20D2, and ZNF800. The presence of histone and integrator complex proteins among the top upregulated hits suggests that FASN silencing may relieve suppression of chromatin organization and transcriptional regulatory machinery in osteosarcoma cells.
Top downregulated proteins: The most strongly downregulated DEPs included NDRG1 (N-myc downstream regulated gene 1), CNTLN (centlein), STON2 (stonin 2), GDF7 (growth differentiation factor 7), HECTD3, HBB (hemoglobin subunit beta), TPM1 (tropomyosin 1), PPP4R4 (serine/threonine protein phosphatase 4 regulatory subunit 4), PTTG1IP (pituitary tumor-transforming gene 1 protein-interacting protein), and PLCB3 (phospholipase C beta 3). The downregulation of NDRG1 is of particular interest because NDRG1 has been reported to suppress tumor growth in multiple cancers, suggesting FASN may normally counteract NDRG1's tumor-suppressive effects.
KEGG pathway enrichment: The top five KEGG pathways enriched among all 567 DEPs were pathways in cancer, ribosome, Huntington's disease, RNA transport, and thermogenesis. The ribosome pathway emerging as the second most significantly enriched pathway was a notable finding, pointing to FASN's involvement in regulating translational machinery in osteosarcoma cells, which was subsequently confirmed by RT-PCR validation of hub ribosomal proteins (UBA52, RPS27, RPS9, RPS18, and RPS28).
Gene Ontology (GO) analysis categorized the 567 DEPs into three functional domains. In the biological processes (BP) category, the most represented terms were metabolic processes, cellular processes, regulation of biological processes, biological regulation, and cellular component organization or biogenesis. In the molecular function (MF) category, DEPs were predominantly annotated to binding, catalytic activity, structural molecular activity, transcription regulator activity, and molecular function regulator. In the cellular component (CC) category, the proteins mapped most often to cell parts, organelles, cells, organelle parts, and membranes.
Interpretation of GO findings: The dominance of metabolic processes and catalytic activity terms is consistent with FASN's primary biochemical role in fatty acid biosynthesis, confirming that the proteomic signal is biologically coherent. The emergence of transcription regulator activity and structural molecular activity among the functional terms points to FASN's broader influence on gene regulatory and cytoskeletal biology in osteosarcoma, effects that extend well beyond the lipid synthesis pathway itself.
PPI network construction: A protein-protein interaction network was built from the String database and visualized using Cytoscape. The network analysis identified hub proteins defined by the highest degree of connectivity (number of interaction edges). UBA52 (Ubiquitin-60S ribosomal protein L40) emerged with the highest degree (83 edges), followed by RPS27 (40S ribosomal protein S27, 43 edges), RPS9 (40S ribosomal protein S9), and RPS18 (40S ribosomal protein S18). These ribosomal proteins form a tightly interconnected cluster within the network, indicating that FASN silencing particularly disrupts the ribosomal protein interaction landscape.
The convergence of KEGG ribosome pathway enrichment, PPI network hub proteins, and subsequent RT-PCR validation in a consistent pattern across all three analytical layers strengthened confidence in the ribosomal connection as a genuine biological effect rather than a statistical artifact. These results suggest FASN may regulate translational capacity in osteosarcoma cells via downstream control of ribosomal proteins, though the mechanistic link between lipid metabolism and ribosome biogenesis requires further investigation.
To move from the full DEP list to a clinically actionable downstream target, the authors applied a multi-step bioinformatic filtering strategy using four independent datasets. List 1 comprised the top 20 downregulated DEPs from the iTRAQ experiment. List 2 was generated from the R2 database by querying which of those 20 proteins showed expression positively correlated with FASN expression across 127 mixed osteosarcoma patient samples (Pearson's correlation). List 3 identified candidates whose high expression was associated with poor prognosis in the same 127-sample R2 cohort using Kaplan-Meier analysis. List 4 confirmed differential expression between 18 OS and paired normal tissues using GEO dataset GSE99671, analyzed by the Wilcoxon rank-sum test.
HNRNPA1 emerges as the top candidate: The intersection (Venn diagram overlap) of these four independently generated lists pointed to HNRNPA1 (heterogeneous nuclear ribonucleoprotein A1) as the protein meeting all selection criteria: it was downregulated upon FASN silencing, its expression positively correlated with FASN in patient data (r = 0.4491, p less than 0.0001 by Pearson correlation in 60 clinical samples), its high expression predicted poor survival in OS patients, and it was overexpressed in OS tissues relative to paired normal bone.
What HNRNPA1 is and why it matters: HNRNPA1 is a member of the heterogeneous nuclear ribonucleoprotein (hnRNP) family, a class of RNA-binding proteins involved in pre-mRNA processing, splicing regulation, mRNA export, and translation modulation. HNRNPA1 has been reported as overexpressed and functionally oncogenic in cervical cancer, gastric cancer, and colorectal cancer. In pancreatic cancer, HNRNPA1 modulates apoptosis-related genes to enhance tumor growth. It is also involved in inducing epithelial-to-mesenchymal transition (EMT) in breast cancer by controlling Cd44 pre-mRNA splicing. Its roles in NF-kB/p52/c-Myc signaling and PEAK-mediated phosphorylation that regulates HNRNPA1 stability were known from other tumor types, but its function in osteosarcoma had not been established.
qRT-PCR and Western blot performed in both 143B and HOS FASN-silenced cells confirmed that HNRNPA1 mRNA and protein levels were reduced when FASN was knocked down. Immunohistochemistry in 71 osteosarcoma clinical specimens demonstrated a significant positive correlation between FASN IHC score and HNRNPA1 IHC score (r = 0.4491, p less than 0.0001), providing direct human tissue evidence that the FASN-HNRNPA1 relationship observed in cell lines translates to patient tumors.
To determine whether HNRNPA1 has clinical relevance in osteosarcoma, the authors analyzed IHC expression data across 71 clinically diagnosed OS tissue specimens from the First Affiliated Hospital of Nanchang University. IHC staining was scored on a composite system multiplying staining intensity (0-3) by percentage of positive cells (0-4), yielding a score range of 0 to 12. Patients were stratified as HNRNPA1-low (score less than 4) or HNRNPA1-high (score 4 or above), and clinical parameters were compared using Pearson's chi-square testing.
Statistically significant clinical associations: HNRNPA1 high expression was significantly associated with three adverse clinical parameters. Tumor size greater than 5 cm showed a markedly higher frequency of HNRNPA1-high expression (56.2%, 27 of 48 cases) compared to tumors 5 cm or smaller (30.4%, 7 of 23 cases), yielding p = 0.047. Distant metastasis was present in 73.7% of HNRNPA1-high cases (14 of 19) versus only 38.5% of HNRNPA1-low cases (20 of 52), with p = 0.015. Advanced Enneking staging (stage IIB or III, denoting locally advanced or distant disease) was associated with HNRNPA1-high expression in 64.5% of cases (20 of 31) versus only 35% in Enneking stage I or IIA (14 of 40), with p = 0.017. No significant associations were found for gender, age, or tumor location (femur/tibia versus elsewhere).
Overall survival impact: Kaplan-Meier survival analysis was performed in a subset of 60 patients for whom follow-up information was available (11 were excluded due to lost follow-up data). Patients with high HNRNPA1 expression showed significantly worse overall survival compared to those with low expression. Independent validation using the R2 database in 127 OS samples confirmed the prognostic relationship between HNRNPA1 levels and overall survival, adding multicohort support for the clinical finding.
These results collectively establish HNRNPA1 as a clinically meaningful prognostic biomarker in osteosarcoma. Its association with tumor size, metastatic status, and Enneking stage, all established prognostic factors in OS, suggests that HNRNPA1 expression reflects the biological aggressiveness of the tumor rather than being an incidental molecular finding.
Having established HNRNPA1 as a downstream effector of FASN with clinical prognostic relevance, the authors performed functional loss-of-function studies to determine whether HNRNPA1 actually drives the malignant behaviors it predicts clinically. Both 143B and HOS osteosarcoma cell lines were stably transfected with lentiviral shRNA targeting HNRNPA1 (shHNRNPA1), and knockdown efficiency was confirmed at both the mRNA level by qRT-PCR and at the protein level by Western blot. A lentiviral control vector (Lv-ctrl) was used as the comparator.
Proliferation and colony formation: CCK-8 assays measuring cell viability at 24, 48, 72, and 96 hours showed a significant reduction in proliferative capacity in HNRNPA1-silenced 143B and HOS cells compared to controls (p less than 0.01 at all time points). Colony formation assays over 8 days in 6-well plates demonstrated significantly fewer and smaller colonies in the HNRNPA1-knockdown groups versus Lv-ctrl, with quantitative analysis confirming the reduction. These results indicate that HNRNPA1 is required for sustained proliferative growth rather than being a passenger in the OS transcriptome.
Migration and invasion: Wound-healing scratch assays showed significantly reduced migration distance at 24 hours in both 143B and HOS HNRNPA1-knockdown cells compared to controls (p less than 0.05), measured by ImageJ software. Transwell migration assays (without Matrigel) and invasion assays (with Matrigel at 1:8 dilution) both demonstrated significantly fewer cells crossing the membrane in HNRNPA1-silenced versus control cells (p less than 0.05 for migration, p less than 0.01 for invasion). Cells in five microscopic fields were counted per condition to ensure representative quantification.
The consistency of HNRNPA1's functional requirement across four different assay systems measuring distinct malignant behaviors, and in two independent OS cell lines, strengthens confidence that HNRNPA1 is a bona fide functional oncogene in osteosarcoma rather than merely a correlative biomarker. The combined in vitro data, together with the clinical associations, justify investigating HNRNPA1 as a therapeutic target in the context of FASN-driven OS biology.
The discussion situates the FASN/HNRNPA1 axis within the broader context of FASN biology in cancer. FASN's oncogenic functions are well documented across tumor types: it promotes cell growth via PGC-1alpha regulation in colorectal cancer, enhances metastasis via EMT induction in ovarian cancer, predicts poor disease-free survival in gastrointestinal stromal tumors (GIST), and improves radiosensitization when inhibited in lung cancer. In osteosarcoma specifically, prior work from this group demonstrated that FASN-mediated anoikis resistance accelerates metastasis via the PI3K/Akt pathway. KEGG analysis in this study highlighted Ras/MAPK signaling as another pathway significantly altered by FASN silencing, expanding the known mechanism landscape beyond PI3K/Akt. This is consistent with emerging reports that FASN suppresses NSCLC malignancies through inactivation of Akt/ERK signaling, suggesting FASN/ERK crosstalk may be a shared mechanism across cancer types.
The HNRNPA1 connection and RNA biology: The authors position HNRNPA1 as a mechanistically plausible downstream target. HNRNPA1 regulates pre-mRNA splicing, mRNA export, and translational control. Its oncogenic roles in cervical, gastric, and colorectal cancer are mediated through control of apoptosis regulators, EMT-related splicing (Cd44 isoform switching in breast cancer), and signaling via NF-kB/p52/c-Myc. In osteosarcoma, the FASN-HNRNPA1 link represents a novel axis connecting lipid metabolic reprogramming to post-transcriptional RNA regulation, a bridge between two hallmarks of cancer biology that have not previously been connected in this tumor type.
Study limitations: The authors acknowledge several important limitations. First, the in vitro experiments were conducted without accompanying in vivo xenograft or animal model validation, leaving open the question of whether HNRNPA1 silencing suppresses tumor growth and metastasis in vivo. Second, the clinical cohort of 71 patients from a single center in China may not generalize to other populations or patient selection criteria. Third, the mechanistic link between FASN and HNRNPA1 is established as correlative and functionally dependent, but the direct molecular pathway by which FASN regulates HNRNPA1 expression (whether through transcriptional, post-transcriptional, or metabolic intermediary mechanisms) was not investigated. Fourth, the absence of miRNA-target gene and TF-target gene regulatory network data limits the completeness of the bioinformatic model.
Despite these limitations, the convergence of iTRAQ discovery, bioinformatic cross-referencing across four independent databases, clinical IHC validation in 71 specimens, and functional cell biology studies positions the FASN/HNRNPA1 axis as a high-priority target for future mechanistic studies and potential therapeutic intervention in osteosarcoma.