Correlation of lipid content and composition with liposarcoma histology and grade

MR-oximetry with fat DESPOT

PURPOSE

The R₁ relaxation rate of fat is a promising marker of tissue oxygenation. Existing techniques to map fat R₁ in MR-oximetry offer limited spatial coverage, require long scan times, or pulse sequences that are not readily available on clinical scanners. This work addresses these limitations with a 3D voxel-wise fat R₁ mapping technique for MR-oximetry based on a variable flip angle (VFA) approach at 3 T.

METHODS

Varying levels of dissolved oxygen (O₂) were generated in a phantom consisting of vials of safflower oil emulsion, used to approximate human fat. Joint voxel-wise mapping of fat and water R₁ was performed with a two-compartment VFA model fitted to multi-echo gradient-echo magnitude data acquired at four flip angles, referred to as Fat DESPOT. Global R₁ was also calculated. Variations of fat, water, and global R₁ were investigated as a function of the partial pressure of O₂ (pO₂). Inversion-prepared stimulated echo magnetic resonance spectroscopy was used as the reference technique for R₁ measurements.

RESULTS

Fat R₁ from Fat DESPOT was more sensitive than water R₁ and global R₁ to variations in pO₂, consistent with previous studies performed with different R₁ mapping techniques. Fat R₁ sensitivity to pO₂ variations with Fat DESPOT (median O₂ relaxivity r_{1, O2} = 1.57× 10^-3 s^-1 mmHg^-1) was comparable to spectroscopy-based measurements for methylene, the main fat resonance (median r_{1, O2}= 1.80 × 10^-3 s^-1 mmHg^-1).

CONCLUSION

Fat and water R₁ can be measured on a voxel-wise basis using a two-component fit to multi-echo 3D VFA magnitude data in a clinically acceptable scan time. Fat and water R₁ measured with Fat DESPOT were sensitive to variations in pO₂. These observations suggest an approach to 3D in vivo MR oximetry.

On the Relevance of Soft Tissue Sarcomas Metabolic Landscape Mapping

Soft tissue sarcomas (STS) prognosis is disappointing, with current treatment strategies being based on a "fit for all" principle and not taking distinct sarcoma subtypes specificities and genetic/metabolic differences into consideration. The paucity of precision therapies in STS reflects the shortage of studies that seek to decipher the sarcomagenesis mechanisms. There is an urge to improve STS diagnosis precision, refine STS classification criteria, and increase the capability of identifying STS prognostic biomarkers. Single-omics and multi-omics studies may play a key role on decodifying sarcomagenesis. Metabolomics provides a singular insight, either as a single-omics approach or as part of a multi-omics strategy, into the metabolic adaptations that support sarcomagenesis. Although STS metabolome is scarcely characterized, untargeted and targeted metabolomics approaches employing different data acquisition methods such as mass spectrometry (MS), MS imaging, and nuclear magnetic resonance (NMR) spectroscopy provided important information, warranting further studies. New chromatographic, MS, NMR-based, and flow cytometry-based methods will offer opportunities to therapeutically target metabolic pathways and to monitorize the response to such metabolic targeting therapies. Here we provide a comprehensive review of STS omics applications, comprising a detailed analysis of studies focused on the metabolic landscape of these tumors.

Characterization of lipomatous tumors with high-resolution 1H MRS at 17.6T: Do benign lipomas, atypical lipomatous tumors and liposarcomas have a distinct metabolic signature?

Background

Distinguishing between some benign lipomas (BLs), atypical lipomatous tumors (ALTs), and dedifferentiated liposarcomas (DDLs) can be challenging due to overlapping magnetic resonance imaging characteristics, and poorly understood molecular mechanisms underlying the malignant transformation of liposarcomas.

Purpose

To identify metabolic biomarkers of the lipomatous tumor spectrum by examining human tissue specimens using high-resolution ¹H magnetic resonance spectroscopy (MRS).

Materials and methods

In this prospective study, human tissue specimens were obtained from participants who underwent surgical resection for radiologically-indeterminate lipomatous tumors between November 2016 and May 2019. Tissue specimens were obtained from normal subcutaneous fat (n=9), BLs (n=10), ALTs (n=7) and DDLs (n=8). Extracts from specimens were examined with high-resolution MRS at 17.6T. Computational modeling of pattern recognition-based cluster analysis was utilized to identify significant differences in metabolic signatures between the lipomatous tumor types.

Results

Significant differences between BLs and ALTs were observed for multiple metabolites, including leucine, valine, branched chain amino acids, alanine, acetate, glutamine, and formate. DDLs were distinguished from ALTs by increased glucose and lactate, and increased phosphatidylcholine. Multivariate principal component analysis showed clear clustering identifying distinct metabolic signatures of the tissue types.

Conclusion

Metabolic signatures identified in ¹H MR spectra of lipomatous tumors provide new insights into malignant progression and metabolic targeting. The metabolic patterns identified provide the foundation of developing noninvasive MRS or PET imaging biomarkers to distinguish between BLs, ALTs, and DDLs.

MDM2-Dependent Rewiring of Metabolomic and Lipidomic Profiles in Dedifferentiated Liposarcoma Models

Dedifferentiated liposarcoma (DDLPS) is an aggressive mesenchymal cancer marked by amplification of MDM2, an inhibitor of the tumor suppressor TP53. DDLPS patients with higher MDM2 amplification have lower chemotherapy sensitivity and worse outcome than patients with lower MDM2 amplification. We hypothesized that MDM2 amplification levels may be associated with changes in DDLPS metabolism. Six patient-derived DDLPS cell line models were subject to comprehensive metabolomic (Metabolon) and lipidomic (SCIEX 5600 TripleTOF-MS) profiling to assess associations with MDM2 amplification and their responses to metabolic perturbations. Comparing metabolomic profiles between MDM2 higher and lower amplification cells yielded a total of 17 differentially abundant metabolites across both panels (FDR < 0.05, log2 fold change < 0.75), including ceramides, glycosylated ceramides, and sphingomyelins. Disruption of lipid metabolism through statin administration resulted in a chemo-sensitive phenotype in MDM2 lower cell lines only, suggesting that lipid metabolism may be a large contributor to the more aggressive nature of MDM2 higher DDLPS tumors. This study is the first to provide comprehensive metabolomic and lipidomic characterization of DDLPS cell lines and provides evidence for MDM2-dependent differential molecular mechanisms that are critical factors in chemoresistance and could thus affect patient outcome.

T2, T2* and spin coupling ratio as biomarkers for the study of lipomatous tumors

BACKGROUND

Subcutaneous fat may have variable signal intensity on T2w images depending on the choice of imaging parameters. However, fatty components within tumors have a different degree of signal dependence on the acquisition scheme. This study examined the use of T2, T2^* relaxometry and spin coupling related signal changes (Spin Coupling ratio, SCr) on two different imaging protocols as clinically relevant descriptors of benign and malignant lipomatous tumors.

MATERIALS AND METHODS

20 patients with benign lipomas or liposarcomas of variable histologic grade were examined at an 1.5 T scanner with Multi Echo Spin Echo (MESE) different echo spacing (ESP) in order to produce bright fat T2w images (ESP: 13.4 ms, 25 equidistant echoes) and dark fat images (ESP: 26.8 ms with 10 equidistant echoes). T2^* relaxometry acquisition comprises 4 sets of in-opposed echoes (2.4-19.2 ms, ESP: 2.4 ms) Multi Echo Gradient Echo (MEGRE) sequence. All parametric maps were calculated on a pixel basis.

RESULTS

Significant differences of SCr were found for five different types of lipomatous tumors (Pairwise t-test with Bonferroni correction): lipomas, well differentiated liposarcomas, myxoid liposarcomas, pleomorphic liposarcomas and poorly differentiated liposarcomas. SCr surpassed the classification performance of T2 and T2^* relaxometry.

DATA CONCLUSION

A novel biomarker based on spin coupling related signal loss, SCr, is indicative of lipomatous tumor histological grading. We concluded that T2, T2^* and SCr can be used for the classification of fat containing tumors, which may be important for biopsy guidance in heterogeneous masses and treatment planning.

Tissue and serum lipidome shows altered lipid composition with diagnostic potential in mycosis fungoides

Mycosis fungoides (MF) is the most common type of cutaneous T cell lymphoma. In this study, we used matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICR-MS) to perform lipidomic profiling of 5 MF tissue samples and 44 serum samples (22 from MF patients and 22 from control subjects). Multivariate statistical analysis of the mass spectral data showed that MF tissues had altered levels of seven lipids and MF sera had altered levels of twelve. Among these, six phosphotidylcholines, PC (34:2), PC (34:1), PC (36:3), PC (36:2), PC (32:0), and PC (38:4) and one sphingomyelin, SM (16:0) were altered in both MF tissues and sera. PC (34:2), PC (34:1), PC (36:3), and PC (36:2) levels were increased in both tissues and sera from MF patients, whereas SM (16:0), PC (32:0), and PC (38:4) levels were increased in MF sera but were decreased in MF tissues. We have thus identified multiple lipids that are altered in MF tissues and sera. This suggests serological and tissue lipidomic profiling could be an effective approach to screening for diagnostic biomarkers of MF.

MLN-8237: A dual inhibitor of aurora A and B in soft tissue sarcomas

Aurora kinases have become an attractive target in cancer therapy due to their deregulated expression in human tumors. Liposarcoma, a type of soft tissue sarcoma in adults, account for approximately 20% of all adult soft tissue sarcomas. There are no effective chemotherapies for majority of these tumors. Efforts made to define the molecular basis of liposarcomas lead to the finding that besides the amplifications of CDK4 and MDM2, Aurora Kinase A, also was shown to be overexpressed. Based on these as well as mathematic modeling, we have carried out a successful preclinical study using CDK4 and IGF1R inhibitors in liposarcoma. MLN8237 has been shown to be a potent and selective inhibitor of Aurora A. MLN-8237, as per our results, induces a differential inhibition of Aurora A and B in a dose dependent manner. At a low nanomolar dose, cellular effects such as induction of phospho-Histone H3 (Ser10) mimicked as that of the inhibition of Aurora kinase A followed by apoptosis. However, micromolar dose of MLN-8237 induced polyploidy, a hallmark effect of Aurora B inhibition. The dose dependent selectivity of inhibition was further confirmed by using siRNA specific inhibition of Aurora A and B. This was further tested by time lapse microscopy of GFP-H2B labelled cells treated with MLN-8237. LS141 xenograft model at a dose of 30 mg/kg also showed efficient growth suppression by selective inhibition of Aurora Kinase A. Based on our data, a dose that can target only Aurora A will be more beneficial in tumor suppression.

The effect of radiotherapy on fat content and fatty acids in myxoid liposarcomas quantified by MRI

BACKGROUND

Myxoid liposarcomas are highly radiosensitive. Consequently radiotherapy is often used pre-operatively to reduce tumor volume and lessen the post-operative deficit. In soft-tissue sarcomas therapy response is mainly evaluated using magnetic resonance imaging (MRI) and the fundamental criterion for a positive response is decreased tumor size. In myxoid liposarcomas an increased fat content is also known to occur as a response to radiotherapy.

OBJECTIVE

To highlight the difficulties of MRI for therapy response evaluation in irradiated myxoid liposarcomas, by using MRI Dixon techniques enabling objective quantification of proton density fat fraction (%) and the number of double bonds (ndb; unsaturation degree) of fatty acids. Secondly, to compare quantitative fat fraction measurements versus visual grading of fat content on T1-weighted images.

CASE DESCRIPTIONS

Prior to surgery, two patients with myxoid liposarcoma were treated with 50Gy. Following radiotherapy, both tumors on MRI showed reduced size, elevated fat fraction and transformed fat fraction histograms with diverse changes of ndb, while histopathological specimens showed discordant treatment effects; one case having good response and the other having poor response.

CONCLUSIONS

A decrease in tumor size and increase in fat content on MRI cannot be interpreted as positive therapy response in radiotherapy of myxoid liposarcomas. Our data also give further supporting evidence that differentiation and maturation of tumor cells is the cause for the lipoma-like areas seen after radiotherapy. Finally, quantitative MRI Dixon techniques are preferable to visual grading for estimating the fat content in lipomatous tumors.

Intraoperative Raman spectroscopy of soft tissue sarcomas

BACKGROUND AND OBJECTIVE

Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated through surgical resection. Current intraoperative margin assessment methods are limited and highlight the need for an improved approach with respect to time and specificity. Here we investigate the potential of near-infrared Raman spectroscopy for the intraoperative differentiation of STS from surrounding normal tissue.

MATERIALS AND METHODS

In vivo Raman measurements at 785 nm excitation were intraoperatively acquired from subjects undergoing STS resection using a probe based spectroscopy system. A multivariate classification algorithm was developed in order to automatically identify spectral features that can be used to differentiate STS from the surrounding normal muscle and fat. The classification algorithm was subsequently tested using leave-one-subject-out cross-validation.

RESULTS

With the exclusion of well-differentiated liposarcomas, the algorithm was able to classify STS from the surrounding normal muscle and fat with a sensitivity and specificity of 89.5% and 96.4%, respectively.

CONCLUSION

These results suggest that single point near-infrared Raman spectroscopy could be utilized as a rapid and non-destructive surgical guidance tool for identifying abnormal tissue margins in need of further excision. Lasers Surg. Med. 48:774-781, 2016. © 2016 Wiley Periodicals, Inc.

Inhibition of polo like kinase 1 in sarcomas induces apoptosis that is dependent on Mcl-1 suppression

Sarcomas are rare cancers and the current treatments in inoperable or metastatic disease have not been shown to prolong survival. In order to develop novel targeted therapies, we tested the efficacy of polo-like kinase 1 (PLK-1) inhibitor (TAK-960) in sarcoma. All the sarcoma cell lines were sensitive to TAK-960 with IC50s in the low nanomolar range. We chose MPNST, CHP100 and LS141 for our studies and of which MPNST cells exclusively underwent polyploidy after a delay in mitosis for about 18 hours; CHP100 cells, after a 24h mitotic delay, died of apoptosis; LS141, after a delay in mitosis stayed at 4N with mild apoptosis. Apoptosis induced by TAK-960 in CHP100 was associated with down-regulation of Mcl-1 and the effect was recapitulated by down-regulating PLK1 by siRNA, confirming that the effect of TAK-960 on Mcl-1 expression is target specific. With suppression of Mcl-1 by siRNA, TAK-960 induced apoptosis in MPNST cells as well. These effects were confirmed in vivo, such that TAK-960 more effectively inhibited CHP100 than MPNST xenografts. In the setting of PLK-1 inhibition, Mcl-1 down regulation is shown to be an important determinant of apoptosis. Collectively, the net effect of this is to drive cells to apoptosis, resulting in a greater anti-tumor effect in vivo. Therefore, targeting PLK-1 should have a greater impact in treating sarcomas provided there is concomitant suppression of Mcl-1. These results further indicate that Mcl-1 could be an important biomarker to predict sensitivity to the induction of apoptosis by PLK-1 targeted therapy in sarcoma.

Metabolomics in the fields of oncology: a review of recent research

The study of all endogenously produced metabolites, known as metabolomics, is the youngest of the "omics" sciences. It is becoming increasingly clear that, of all of the "omics" techniques, metabolomic approaches will become increasingly useful in disease diagnosis and have potential power to improve our understanding of the underlying mechanisms of cancer. The primary aim of the review is to discuss the relationship between metabolomics and tumors are elucidated in detail. Then the review is also to introduce the technologies of metabolomics, especially emphasizing the application of metabolomics in the fields of oncology.

Multicentric infiltrative lipoma in a farmed Mediterranean seabass Dicentrarchus labrax: a pathological and biochemical case study

A tumour diagnosed as multicentric infiltrative lipoma affecting a single farmed seabass is described. The fish had 3 masses on the lateral side of its back, deforming the skin surface. The masses showed a tendency to invade the underlying musculature. Histologically, the neoplasm consisted of differentiated adipocytes. Biochemically, the neoplastic tissue showed lower values of monounsaturated fatty acids and higher values of polyunsaturated fatty acids compared with adjacent normal muscular tissue, particularly of the n3 series, such as eicosapentanoic (C20:5n3) and docosahexanoic (C22:6n3) acids. Data obtained suggest a metabolic disturbance in the lipid component of the muscular tissue metabolic pathway, which could be the starting point to promote lipoma formation. This is the first report of lipoma in Mediterranean seabass.

Statistical classification strategy for proton magnetic resonance spectra of soft tissue sarcoma: an exploratory study with potential clinical utility

Purpose: Histological grading is currently one of the best predictors of tumor behavior and outcome in soft tissue sarcoma. However, occasionally there is significant disagreement even among expert pathologists. An alternative method that gives more reliable and non-subjective diagnostic information is needed. The potential use of proton magnetic resonance spectroscopy in combination with an appropriate statistical classification strategy was tested here in differentiating normal mesenchymal tissue from soft tissue sarcoma.

Methods: Fifty-four normal and soft tissue sarcoma specimens of various histological types were obtained from 15 patients. One-dimensional proton magnetic resonance spectra were acquired at 360 MHz. Spectral data were analyzed by using both the conventional peak area ratios and a specific statistical classification strategy.

Results: The statistical classification strategy gave much better results than the conventional analysis. The overall classification accuracy (based on the histopathology of the MRS specimens) in differentiating normal mesenchymal from soft tissue sarcoma was 93%, with a sensitivity of 100% and specificity of 88%.The results in the test set were 83, 92 and 76%, respectively. Our optimal region selection algorithm identified six spectral regions with discriminating potential, including those assigned to choline, creatine, glutamine, glutamic acid and lipid.

Conclusion: Proton magnetic resonance spectroscopy combined with a statistical classification strategy gave good results in differentiating normal mesenchymal tissue from soft tissue sarcoma specimens ex vivo. Such an approach may also differentiate benign tumors from malignant ones and this will be explored in future studies.

Metabonomics and its application in oncobiology research

The primary aim of this review is to introduce the research status of metabonomics/metabolomics and the application of metabonomics in oncobiology research. At first, the concept of metabonomics and the relationship between metabonomics and tumors are elucidated in detail. Then the research technologies of metabonomics in oncobiology are introduced. Finally, the latest advances in the application of metabonomics in early diagnosis, treatment and prognosis of tumors are summarized.

A developmental model of sarcomagenesis defines a differentiation-based classification for liposarcomas

The importance of adult stem cells in the development of neoplastic diseases is becoming increasingly well appreciated. We hypothesized that sarcomas of soft tissue could be categorized by their developmental/differentiation status from stem cell to mature tissue, similar to the hematological malignancies. We conducted gene expression analyses during in vitro differentiation of human mesenchymal stem cells into adipose tissue, as a representative mature connective tissue, and identified genes whose expression changed significantly during adipogenesis. Gene clustering and distance correlation analysis allowed the assignment of a unique time point during adipogenesis that strongly correlates to each of the four major liposarcoma subtypes. Using a novel gene expression strategy, in which liposarcomas are compared to their corresponding adipocytic maturing cells, we identified a group of genes overexpressed in liposarcomas that indicate the stage of differentiation arrest, ie, sharing a similar expression profile to adipocytic cells at a corresponding stage of differentiation, and a distinct set of genes overexpressed in liposarcomas that are not found in the corresponding stage of differentiation. We propose that the latter set is enriched for candidate transformation-associated genes. Our results indicate that a degree of developmental maturity can be quantitatively assigned to solid tumors, supporting the notion that transformation of a solid tumor stem cell can occur at distinct stages of maturation.

New diagnostic modalities in soft tissue sarcoma

Molecular and cytogenetic analysis of soft tissue sarcoma has provided a vast amount of new genetic information over the past 10 years. Recent advances in genetic technology, such as fluorescence in situ hybridization (FISH), reverse transcriptase-polymerase chain reaction (RT-PCR), and positional cloning techniques have greatly increased the rate of new discoveries and soon may bring cytogenetic and molecular analysis to standard pathology laboratories. Karotypic analysis of soft tissue tumors have demonstrated specific cytogenetic aberrations which have proved to be extremely useful diagnostically and have solidified and improved soft tissue tumor classification systems. Objective and reproducible prognostication in soft tissue sarcoma remains problematic. Presently, the grade and size of the sarcoma are the most important factors used to estimate risk of relapse and overall survival. Assigning a pathologic grade to an individual sarcoma as a means of predicting clinical behavior is often difficult with a 40% discordance rate even between expert sarcoma pathologists. There is mounting evidence that the composition of membrane phospholipid in tumor tissue is an important indicator of a tumor's cellularity, proliferative capacity, and differentiation state. However, there is a lack of information on the biochemical determinants of sarcoma proliferation and differentiation. To address these problems, novel quantitative ex vivo nuclear magnetic resonance (NMR) methods have been applied to determine the biochemical changes in tissue lipid for soft tissue sarcoma. The biochemical changes in tissue lipid have been found to correlate with sarcoma cellularity, growth rate, and differentiation. Continued prospective NMR analysis of tissue lipid biochemistry in soft tissue tumors will permit the development of a clinically relevant biochemical system of prognostic determinants for soft tissue sarcoma in the future.