Global Journal of Science Frontier Research, G: Bio-Tech & Genetics, Volume 22 Issue 2

across a diverse set of tumors, the authors found that for patients (n=40) with three or more longitudinal time points the patient-specific ctDNA had a correlation with tumor burden in 16/19 (85%) patients with partial response and overall in 27/40 (68%) patients 162 . On the other hand, use of cancer antigens only correlated with tumor burden in 19/40 (47.5%) patients, suggesting a lower utility than patient-specific ctDNA. Outside of somatic mutations, detection of DNA methylation in ctDNA may offer an alternative modality for monitoring tumor burden and recurrence. Whole- genome bisulfite sequencing (WGBS) can detect DNA methylation throughout the genome. Importantly, methylation patterns greatly differ between malignant and normal cells, and could be used to distinguish between different cancer types. Certain sarcomas, such as synovial sarcomas, had unique methylation patterns that was relatively uniform 8 . On the other hand, DDLPS had 3-4 methylation patterns that overlapped with undifferentiated pleomorphic sarcoma and gynecologic leiomyosarcoma. Nonetheless, detecting methylation in ctDNA has utility for monitoring tumor burden. The Circulating Cell-free Genome Atlas (CCGA; NCT02889978)is a prospective, multi-center, observa- tional study that uses machine learning to detect cancer type and tumor burden from ctDNA 163 . By WGBS, methylation signatures could robustly identify several cancer types with high specificity. Importantly, they found that WGBS of ctDNA outperformed WGS, which detected somatic mutations, and targeted mutation panels in classifying cancer types. Because methylation is more pervasive than mutations, it may enable lower limits of detection compared to detection limits for somatic mutations detected through WGS or targeted ctDNA panels 164 . A clear limitation in this study is the small number of sarcoma patients included. Another limitation is that not all participants were asymptomatic, could inform the utility of DNA methylation for disease monitoring. Studies including asymptomatic patients were still ongoing. X. S ummary In summary, WDLPS, DDLPS and PLPS have complex genomics due to either formation or propagation of neochromosomes or complex rearrangements and copy number alterations. These mutations lead to high levels of heterogeneity generating mixed tumor phenotypes, which can be difficult to classify. The altered genes, which are selected for during tumor evolution, drive the perpetual survival and continued growth of immature or poorly differentiated dipocytes. Unlike the other liposarcoma subtypes, MLPS is characterized by a translocation, where the N-terminal partner, DDIT3, in a healthy context plays an important role in regulating adipogenic differentiation. However, in the setting of MLPS, the fusion protein may instead act as an aberrant transcription factor inhibiting adipogens is and maintaining immature adipocyte. In addition to genetic alterations, tumor development and formation may be influenced by exogenous factors including surrounding the tissue microenvironments and tissue inflammatory state as well as endogenous factors including TP53 , RB1 , and PI3K/AKT/PTEN pathways. A summary of the current therapies against these drivers and other genes are reviewed in Keung and Somaiah and Tyler et al. 70,165 . Overall, the severity of disease appears to be strongly influenced by higher degrees of genetic alterations and poorer differentiation. Insights into mechanisms of phenotypic plasticity – dedifferentiation or blocked differentiation – may enable better understanding on how to control differentiation in liposarcoma therapeutically. It is important to note that phenotypic plasticity is not a novel invention by cancer cells but rather a co-opt of latent mechanisms that are used by healthy cells to support tissue homeostasis 166 . The latest developments in tools and technologies, including SCS and ctDNA, will be fundamental in advancing biology, diagnostics, and molecular therapeutics. SCS may shed light on intertumoral heterogeneity and identify subclones with actionable gene targets. Utilizing ctDNA may enable a feasible method for diagnosis and disease monitoring where recurrence is a possibility. Most importantly, continued exploration of the genomics of liposarcoma should enable advances in drug development centered on the genetic alterations. A cknowledgements To Jing Zheng for SEER investigation. To Andrew Ibrahim, and Enes Kelestemur for reviews. All original figures were generated in BioRender.com. R eferences R éférences R eferencias 1. Taylor, B. S. et al. Advances in sarcoma genomics and new therapeutic targets. Nat Rev Cancer 11, 541-557, doi:10.1038/nrc3087 (2011). 2. Stanelle, E. J. et al. Prognostic factors and survival in pediatric and adolescent liposarcoma. Sarcoma 2012, 870910, doi: 10.1155/2012/870910 (2012). 3. Oh, Y. J. et al. Prognostic Model to Predict Survival Outcome for Curatively Resected Liposarcoma: A Multi-Institutional Experience. J Cancer 7, 1174- 1180, doi: 10.7150/jca.15243 (2016). 4. Knebel, C. et al. Prognostic factors and outcome of Liposarcoma patients: a retrospective evaluation over 15 years. BMC Cancer 17, 410, doi: 10.1186/s 12885-017-3398-y (2017). 5. Schwartz, S. A. & Centurion, S. A. (Medscape, 2019). 6. Alaggio, R. et al. Liposarcomas in young patients: a study of 82 cases occurring in patients younger © 2022 Global Journals 1 Year 2022 26 Global Journal of Science Frontier Research Volume XXII Issue ersion I VII ( G ) The Genomics of Liposarcoma: A Review and Commentary