Secondary lymphedema (LE) develops after injury to lymphatic vasculature from infection, surgery, or cancer treatment and is characterized by fluid stasis, immune activation, and fibroadipose deposition. Omics approaches—transcriptomics, proteomics, metabolomics, lipidomics, and genomic or computational methods—enable systems-level characterization of inflammatory, fibrotic, metabolic, vascular, and genetic programs that underlie disease onset and progression. This review summarizes published omics studies applied specifically to secondary LE, highlights candidate biomarkers, implicated cell populations and signaling pathways, notes methodological limitations of existing datasets and pipelines, and outlines multi-omics strategies to advance diagnosis, risk stratification, and therapeutic discovery.
Secondary LE is a chronic, debilitating disorder without approved pharmacologic therapies. The disease involves lymphatic vessel injury, subsequent fluid stasis, immune activation, and progressive fibroadipose remodeling. The NIH workshop “Yet to be Charted: Lymphatic System in Health and Disease” identified application of advanced omics as a priority for the field. Omics platforms provide comprehensive datasets that can inform biomarker discovery, stratify risk, monitor treatment response, and nominate therapeutic targets. While omics has been applied broadly to lymphatic biology (for example, lymph fluid proteomics), there are fewer studies focused on secondary LE. The literature summarized here evaluates how different omics modalities and sample types have been used to interrogate the pathophysiology of secondary LE and what translational insights have emerged.
Transcriptomics studies in secondary LE have analyzed multiple sample types including adipose tissue, skin, collecting lymphatic vessel cells (LECs and LMCs), and circulating blood cells. Techniques reported include bulk RNA sequencing, single-nucleus RNA-seq (sNuc-seq), and single-cell RNA-seq (scRNA-seq). Across adipose tissue studies, common themes are upregulation of inflammatory and chemotactic pathways and alterations in lymphatic vascular signaling.
Several human studies comparing paired affected and unaffected limbs in breast cancer–related lymphedema (BCRL) report increased expression of inflammatory response, chemotaxis, and angiogenesis genes in LE tissue, with decreased expression of epidermal differentiation and cell-junction genes. Specific genes repeatedly identified across studies include IL6, VEGFC, FLT4, PTX3, AREG, and extracellular matrix–related genes such as TNC and ADAMTS family members.
Some transcriptomic analyses have focused on lipid-metabolism and lipolytic enzyme families. For example, differential expression of sPLA2 family members (PLA2G2A and PLA2G5) has been observed, and sPLA2-producing macrophages were implicated in lymphatic endothelial cell dysfunction. Other datasets report extensive differentially expressed genes with pathway analyses highlighting downregulation of PPARG signaling in LE adipose tissue; follow-up work linked EZH2 as an epigenetic regulator of PPARγ, and inhibition of the EZH2–PPARγ axis reduced fibroadipose tissue in experimental models described by the source.
Single-cell and single-nucleus studies have revealed cellular heterogeneity in adipose stromal vascular fractions, identified adipose-derived stem cell and mesenchymal stem cell populations, and characterized LEC and LMC transcriptional profiles in collecting vessels. Transcriptomic findings have informed mechanistic follow-up in animal models, including modulation of TIE2/TEK signaling to reduce LE in experimental systems.
Genomic approaches summarized include whole-exome sequencing (WES) in individuals with suspected primary lymphatic disorders to contextualize susceptibility to secondary LE, as well as targeted SNP and genetic association analyses in cohorts evaluating risk for BCRL. Family-based WES studies and cohort analyses have been used to explore germline variants that may increase risk for primary or acquired LE. The review highlights that genetic profiling can identify candidate susceptibility loci but also notes that studies vary in design, sample size, and focus between primary and secondary LE contexts.
Proteomic studies in secondary LE examine lymph fluid, serum, platelets, and tissue specimens. Reported protein candidates span barrier and structural proteins (e.g., filaggrin, fibronectin 1), components of the renin–angiotensin system (angiotensinogen), apolipoproteins (ApoE), complement factors, and proteases such as cathepsin D. Proteomics has been applied to paired limb tissue, to pre- and post-procedural serum samples (for example, before and after lymphaticovenous anastomosis), and to comparisons among LE, lipedema, and obesity cohorts. These datasets aim to define circulating or tissue-based protein signatures of LE, monitor therapeutic interventions, and suggest pathways for targeted therapies.
Metabolomic analyses of serum and tissue in LE cohorts have identified altered small-molecule profiles including steroid and eicosanoid metabolites and amino-acid–related changes. Examples mentioned across reviewed datasets include corticosterone, leukotriene-related metabolites, prostaglandin E3, and branched-chain amino acids such as valine. The authors emphasize that metabolite levels are highly influenced by extrinsic and clinical factors—diet, medications, body-mass index, renal and hepatic function, infection/inflammation, and timing of sample collection—so metabolomic signals must be interpreted within the clinical context rather than assumed disease-specific markers in isolation.
Lipidomic profiling in LE tissues and serum has reported changes in lipid classes and species, including alterations in LDL-C and HDL-C fractions and fatty acids such as arachidonic acid and eicosapentaenoic acid. Fatty-acid analyses of adipose tissue samples have been conducted to delineate lipid remodeling associated with fibroadipose deposition. As with metabolomics, lipidomic findings are subject to confounding by diet, metabolic state, and prior therapies.
The cumulative omics literature in secondary LE provides convergent evidence for inflammatory, lymphangiogenic, immune, metabolic, and fibrotic programs driving disease. Candidate biomarkers and therapeutic targets have emerged from transcriptomic, proteomic, metabolomic, and lipidomic datasets, and genomic studies offer insight into susceptibility. However, current work is limited by heterogeneous sample types, small cohorts, variable platforms, and differing bioinformatic pipelines. The authors advocate for future multi-omics strategies that integrate transcriptomic, proteomic, metabolomic, lipidomic, and genomic data across well-characterized clinical cohorts with standardized sampling and analytic methods to enable diagnostic biomarker development, risk stratification, and treatment discovery for secondary LE.