Hierarchical clustering of flow cytometry data for the study of conventional central chondrosarcoma

An exploratory study of cell stiffness as a mechanical label-free biomarker across multiple musculoskeletal sarcoma cells

BACKGROUND

Cancer cells are characterized by changes in cell cytoskeletal architecture and stiffness. Despite advances in understanding the molecular mechanisms of musculoskeletal cancers, the corresponding cellular mechanical properties remain largely unexplored. The aim of this study was to investigate the changes in cellular stiffness and the associated cytoskeleton configuration alterations in various musculoskeletal cancer cells.

METHODS

Cell lines from five main sarcoma types of the musculoskeletal system (chondrosarcoma, osteosarcoma, Ewing sarcoma, fibrosarcoma and rhabdomyosarcoma) as well as their healthy cell counterparts (chondrocytes, osteoblasts, mesenchymal stem cells, fibroblasts, skeletal muscle cells) were subjected to cell stiffness measurements via atomic force microscopy (AFM). Biochemical and structural changes of the cytoskeleton (F-actin, β-tubulin and actin-related protein 2/3) were assessed by means of fluorescence labelling, ELISA and qPCR.

RESULTS

While AFM stiffness measurements showed that the majority of cancer cells (osteosarcoma, Ewing sarcoma, fibrosarcoma and rhabdomyosarcoma) were significantly less stiff than their corresponding non-malignant counterparts (p < 0.001), the chondrosarcoma cells were significant stiffer than the chondrocytes (p < 0.001). Microscopically, the distribution of F-actin differed between malignant entities and healthy counterparts: the organisation in well aligned stress fibers was disrupted in cancer cell lines and the proteins was mainly concentrated at the periphery of the cell, whereas β-tubulin had a predominantly perinuclear localization. While the F-actin content was lower in cancer cells, particularly Ewing sarcoma (p = 0.018) and Fibrosarcoma (p = 0.023), this effect was even more pronounced in the case of β-tubulin for all cancer-healthy cell duos. Interestingly, chondrosarcoma cells were characterized by a significant upregulation of β-tubulin gene expression (p = 0.005) and protein amount (p = 0.032).

CONCLUSION

Modifications in cellular stiffness, along with structural and compositional cytoskeleton rearrangement, constitute typical features of sarcomas cells, when compared to their healthy counterpart. Notably, whereas a decrease in stiffness is typically a feature of malignant entities, chondrosarcoma cells were stiffer than chondrocytes, with chondrosarcoma cells exhibiting a significantly upregulated β-tubulin expression. Each Sarcoma entity may have his own cellular-stiffness and cytoskeleton organisation/composition fingerprint, which in turn may be exploited for diagnostic or therapeutic purposes.

Cell surface markers for mesenchymal stem cells related to the skeletal system: A scoping review

Multipotent mesenchymal stromal cells (MSCs) have been described as bone marrow stromal cells, which can form cartilage, bone or hematopoietic supportive stroma. In 2006, the International Society for Cell Therapy (ISCT) established a set of minimal characteristics to define MSCs. According to their criteria, these cells must express CD73, CD90 and CD105 surface markers; however, it is now known they do not represent true stemness epitopes. The objective of the present work was to determine the surface markers for human MSCs associated with skeletal tissue reported in the literature (1994-2021). To this end, we performed a scoping review for hMSCs in axial and appendicular skeleton. Our findings determined the most widely used markers were CD105 (82.9%), CD90 (75.0%) and CD73 (52.0%) for studies performed in vitro as proposed by the ISCT, followed by CD44 (42.1%), CD166 (30.9%), CD29 (27.6%), STRO-1 (17.7%), CD146 (15.1%) and CD271 (7.9%) in bone marrow and cartilage. On the other hand, only 4% of the articles evaluated in situ cell surface markers. Even though most studies use the ISCT criteria, most publications in adult tissues don't evaluate the characteristics that establish a stem cell (self-renewal and differentiation), which will be necessary to distinguish between a stem cell and progenitor populations. Collectively, MSCs require further understanding of their characteristics if they are intended for clinical use.

Biological Heterogeneity of Chondrosarcoma: From (Epi) Genetics through Stemness and Deregulated Signaling to Immunophenotype

Chondrosarcoma (ChS) is a primary malignant bone tumor. Due to its heterogeneity in clinical outcomes and resistance to chemo- and radiotherapies, there is a need to develop new potential therapies and molecular targets of drugs. Many genes and pathways are involved in in ChS progression. The most frequently mutated genes are isocitrate dehydrogenase ½ (IDH1/2), collagen type II alpha 1 chain (COL2A1), and TP53. Besides the point mutations in ChS, chromosomal aberrations, such as 12q13 (MDM2) amplification, the loss of 9p21 (CDKN21/p16/INK4A and INK4A-p14ARF), and several gene fusions, commonly occurring in sarcomas, have been found. ChS involves the hypermethylation of histone H3 and the decreased methylation of some transcription factors. In ChS progression, changes in the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K-AKT-mTOR) and hedgehog pathways are known to play a role in tumor growth and chondrocyte proliferation. Due to recent discoveries regarding the potential of immunotherapy in many cancers, in this review we summarize the current state of knowledge concerning cellular markers of ChS and tumor-associated immune cells. This review compares the latest discoveries in ChS biology from gene alterations to specific cellular markers, including advanced molecular pathways and tumor microenvironment, which can help in discovering new potential checkpoints in inhibitory therapy.

The oncometabolite R-2-hydroxyglutarate dysregulates the differentiation of human mesenchymal stromal cells via inducing DNA hypermethylation

Background

Isocitrate dehydrogenase (IDH1/2) gene mutations are the most frequently observed mutations in cartilaginous tumors. The mutant IDH causes elevation in the levels of R-enantiomer of 2-hydroxylglutarate (R-2HG). Mesenchymal stromal cells (MSCs) are reasonable precursor cell candidates of cartilaginous tumors. This study aimed to investigate the effect of oncometabolite R-2HG on MSCs.

Methods

Human bone marrow MSCs treated with or without R-2HG at concentrations 0.1 to 1.5 mM were used for experiments. Cell Counting Kit-8 was used to detect the proliferation of MSCs. To determine the effects of R-2HG on MSC differentiation, cells were cultured in osteogenic, chondrogenic and adipogenic medium. Specific staining approaches were performed and differentiation-related genes were quantified. Furthermore, DNA methylation status was explored by Illumina array-based arrays. Real-time PCR was applied to examine the signaling component mRNAs involved in.

Results

R-2HG showed no influence on the proliferation of human MSCs. R-2HG blocked osteogenic differentiation, whereas promoted adipogenic differentiation of MSCs in a dose-dependent manner. R-2HG inhibited chondrogenic differentiation of MSCs, but increased the expression of genes related to chondrocyte hypertrophy in a lower concentration (1.0 mM). Moreover, R-2HG induced a pronounced DNA hypermethylation state of MSC. R-2HG also improved promotor methylation of lineage-specific genes during osteogenic and chondrogenic differentiation. In addition, R-2HG induced hypermethylation and decreased the mRNA levels of SHH, GLI1and GLI2, indicating Sonic Hedgehog (Shh) signaling inhibition.

Conclusions

The oncometabolite R-2HG dysregulated the chondrogenic and osteogenic differentiation of MSCs possibly via induction of DNA hypermethylation, improving the role of R-2HG in cartilaginous tumor development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-020-07744-x.

Prognostic biomarkers related to breast cancer recurrence identified based on Logit model analysis

BACKGROUND

This study intended to determine important genes related to the prognosis and recurrence of breast cancer.

METHODS

Gene expression data of breast cancer patients were downloaded from TCGA database. Breast cancer samples with recurrence and death were defined as poor disease-free survival (DFS) group, while samples without recurrence and survival beyond 5 years were defined as better DFS group. Another gene expression profile dataset (GSE45725) of breast cancer was downloaded as the validation data. Differentially expressed genes (DEGs) were screened between better and poor DFS groups, which were then performed function enrichment analysis. The DEGs that were enriched in the GO function and KEGG signaling pathway were selected for cox regression analysis and Logit regression (LR) model analysis. Finally, correlation analysis between LR model classification and survival prognosis was analyzed.

RESULTS

Based on the breast cancer gene expression profile data in TCGA, 540 DEGs were screened between better DFS and poor DFS groups, including 177 downregulated and 363 upregulated DEGs. A total of 283 DEGs were involved in all GO functions and KEGG signaling pathways. Through LR model screening, 10 important feature DEGs were identified and validated, among which, ABCA3, CCL22, FOXJ1, IL1RN, KCNIP3, MAP2K6, and MRPL13, were significantly expressed in both groups in the two data sets. ABCA3, CCL22, FOXJ1, IL1RN, and MAP2K6 were good prognostic factors, while KCNIP3 and MRPL13 were poor prognostic factors.

CONCLUSION

ABCA3, CCL22, FOXJ1, IL1RN, and MAP2K6 may serve as good prognostic factors, while KCNIP3 and MRPL13 may be poor prognostic factors for the prognosis of breast cancer.

Identification of promising prognostic genes for relapsed acute lymphoblastic leukemia

PURPOSE

The present study aimed to identify the molecular mechanism of acute lymphoblastic leukemia (ALL), and explore valuable prognostic biomarkers for relapsed ALL.

METHODS

Gene expression dataset including 59 samples from ALL survivals without recurrence (good group) and 114 samples from dead ALL patients died of recurrence (poor group) was downloaded from TCGA database. The differentially expressed genes (DEGs) were identified between good and poor groups, followed by pathway and functional enrichment analyses. Subsequently, logistic regression model and survival analysis were performed.

RESULTS

In total, 637 up- and 578 down-regulated DEGs were revealed between good and poor groups. These DEGs were mainly enriched in functions including transcription and pathways like focal adhesion. Genes including alpha-protein kinase 1 (ALPK1), zinc finger protein 695 (ZNF695), actinin alpha 4 (ACTN4), calreticulin (CALR), and F-Box and leucine rich repeat protein 5 (FBXL5) were outstanding in survival analysis.

CONCLUSION

Transcription and focal adhesion might play important roles in ALL progression. Furthermore, genes including ALPK1, ZNF695, ACTN4, CALR, and FBXL5 might be novel prognostic genes for relapsed ALL.

Chondrosarcoma: A Rare Misfortune in Aging Human Cartilage? The Role of Stem and Progenitor Cells in Proliferation, Malignant Degeneration and Therapeutic Resistance

Unlike other malignant bone tumors including osteosarcomas and Ewing sarcomas with a peak incidence in adolescents and young adults, conventional and dedifferentiated chondrosarcomas mainly affect people in the 4th to 7th decade of life. To date, the cell type of chondrosarcoma origin is not clearly defined. However, it seems that mesenchymal stem and progenitor cells (MSPC) in the bone marrow facing a pro-proliferative as well as predominantly chondrogenic differentiation milieu, as is implicated in early stage osteoarthritis (OA) at that age, are the source of chondrosarcoma genesis. But how can MSPC become malignant? Indeed, only one person in 1,000,000 will develop a chondrosarcoma, whereas the incidence of OA is a thousandfold higher. This means a rare coincidence of factors allowing escape from senescence and apoptosis together with induction of angiogenesis and migration is needed to generate a chondrosarcoma. At early stages, chondrosarcomas are still assumed to be an intermediate type of tumor which rarely metastasizes. Unfortunately, advanced stages show a pronounced resistance both against chemo- and radiation-therapy and frequently metastasize. In this review, we elucidate signaling pathways involved in the genesis and therapeutic resistance of chondrosarcomas with a focus on MSPC compared to signaling in articular cartilage (AC).

Identifying heterogeneous subtypes of gastric cancer and subtype‑specific subpaths of microRNA‑target pathways

The present study aimed to classify gastric cancer (GC) into subtypes and to screen the subtype-specific genes, their targeted microRNAs (miRNAs) and enriched pathways to explore the putative mechanism of each GC subtypes. The GSE13861 data set was downloaded from the Gene Expression Omnibus and used to screen differential expression genes (DEGs) in GC samples based on the detection of imbalanced differential signal algorithm. The specific genes in each subtype were identified with the cut-off criterion of U>0.04, pathway enrichment analysis was performed and the subtype-specific subpaths of miRNA-target pathway were determined. A total of 1,263 DEGs were identified in the primary gastric adenocarcinoma (PGD) samples, which were subsequently divided into four subtypes, according to the hierarchy cluster analysis. Identification of the subpaths of each subtype indicated that the subpath related to subtype 1 was miRNA (miR)-202/calcium voltage-gated channel subunit α1 (CACNA1E)/type II diabetes mellitus. The nuclear factor-κB signaling pathway was the most significantly specific pathway and subpath identified for subtype 2, which was regulated by miR-338-targeted suppression of C-C motif chemokine ligand 21 (CCL21). For subtype 3, significant related pathways included ubiquitin-mediated proteolysis and proteasome, and the important subpath was miR-146B/proteasome 26S subunit, non-ATPase 3 (PSMD3)/proteasome; focal adhesion was the significant pathway indicated for subtype 4, and the subpaths were miR-34A/vinculin (VCL)/focal adhesion and miR-34C/VCL/focal adhesion. In addition, Helicobacter pylori infection was higher in GC subtype 1 than in other subtypes. Specific genes, such as CACNA1E, CCL21, PSMD3 and VCL, may be used as potential feature genes to identify different subtypes of GC, and their associated subpaths may partially explain the pathogenetic mechanism of each GC subtype.

Significant distinct branches of hierarchical trees: a framework for statistical analysis and applications to biological data

Background

One of the most common goals of hierarchical clustering is finding those branches of a tree that form quantifiably distinct data subtypes. Achieving this goal in a statistically meaningful way requires (a) a measure of distinctness of a branch and (b) a test to determine the significance of the observed measure, applicable to all branches and across multiple scales of dissimilarity.

Results

We formulate a method termed Tree Branches Evaluated Statistically for Tightness (TBEST) for identifying significantly distinct tree branches in hierarchical clusters. For each branch of the tree a measure of distinctness, or tightness, is defined as a rational function of heights, both of the branch and of its parent. A statistical procedure is then developed to determine the significance of the observed values of tightness. We test TBEST as a tool for tree-based data partitioning by applying it to five benchmark datasets, one of them synthetic and the other four each from a different area of biology. For each dataset there is a well-defined partition of the data into classes. In all test cases TBEST performs on par with or better than the existing techniques.

Conclusions

Based on our benchmark analysis, TBEST is a tool of choice for detection of significantly distinct branches in hierarchical trees grown from biological data. An R language implementation of the method is available from the Comprehensive R Archive Network: http://www.cran.r-project.org/web/packages/TBEST/index.html.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1000) contains supplementary material, which is available to authorized users.

Automatic B cell lymphoma detection using flow cytometry data

Background

Flow cytometry has been widely used for the diagnosis of various hematopoietic diseases. Although there have been advances in the number of biomarkers that can be analyzed simultaneously and technologies that enable fast performance, the diagnostic data are still interpreted by a manual gating strategy. The process is labor-intensive, time-consuming, and subject to human error.

Results

We used 80 sets of flow cytometry data from 44 healthy donors, 21 patients with chronic lymphocytic leukemia (CLL), and 15 patients with follicular lymphoma (FL). Approximately 15% of data from each group were used to build the profiles. Our approach was able to successfully identify 36/37 healthy donor cases, 18/18 CLL cases, and 12/13 FL cases.

Conclusions

This proof-of-concept study demonstrated that an automated diagnosis of CLL and FL can be obtained by examining the cell capture rates of a test case using the computational method based on the multi-profile detection algorithm. The testing phase of our system is efficient and can facilitate diagnosis of B-lymphocyte neoplasms.

Advances in human B cell phenotypic profiling

To advance our understanding and treatment of disease, research immunologists have been called-upon to place more centralized emphasis on impactful human studies. Such endeavors will inevitably require large-scale study execution and data management regulation (“Big Biology”), necessitating standardized and reliable metrics of immune status and function. A well-known example setting this large-scale effort in-motion is identifying correlations between eventual disease outcome and T lymphocyte phenotype in large HIV-patient cohorts using multiparameter flow cytometry. However, infection, immunodeficiency, and autoimmunity are also characterized by correlative and functional contributions of B lymphocytes, which to-date have received much less attention in the human Big Biology enterprise. Here, we review progress in human B cell phenotyping, analysis, and bioinformatics tools that constitute valuable resources for the B cell research community to effectively join in this effort.

Toward new insights on the white blood cell differential by flow cytometry: a proof of concept study on the sepsis model

BACKGROUND

We sought to evaluate, on a model of sepsis, the clinical relevance of new parameters obtained on a white blood cell (WBC) differential by flow cytometry, implemented in the routine workflow of our hematology laboratory.

METHODS

A WBC with differential by flow cytometry was done on 459 patients at admission in intensive care unit. They were retrospectively categorized in having (i) infection or not or (ii) a high gravity score (severe sepsis or septic shock) or not. We analyzed by hierarchical clustering, in a multidimensional manner, 50 parameters provided by the flow cytometric platform in place of the standard seven parameters for a standard differential.

RESULTS

Our approach allows to discriminate on the basis of a WBC differential (i) infected patients at admission based on a 16 parameter signature, with a concordance rate of 72.7% and a specificity of 79.9% and (ii) patients with high gravity score (septic shock or severe sepsis) at admission with a signature of eight parameters, with a concordance rate of 74.7% and a specificity of 75.9%.

CONCLUSIONS

This study shows the clinical relevance of an extended WBC differential to obtain by a flow cytometer integrated into a routine hematology laboratory workflow. Development of such approach implicates the redefinition of the WBC differential by integrating new parameters.

Multiparameter flow cytometry and bioanalytics for B cell profiling in systemic lupus erythematosus

B lymphocyte involvement in systemic lupus erythematosus has been recognized for several decades, mainly in the context of autoantibody production. Both mouse and human studies reveal that different types of antibody responses, as well as antibody-independent effector functions can be ascribed to distinct subpopulations (subsets) of circulating B cells. Characterizing human B cell subsets can advance the field of autoimmunity even further by establishing B cell signatures associated with disease severity, progression, and response-to-treatment. For this purpose, we have developed specialized B cell reagent panels for multiparameter flow cytometry, and combine their use with advanced bioinformatics strategies that together will likely be advantageous for improving the characterization, prognosis, and for possibly improving treatment regimens of chronic inflammatory diseases such as lupus.

The Bone Niche of Chondrosarcoma: A Sanctuary for Drug Resistance, Tumour Growth and also a Source of New Therapeutic Targets

Chondrosarcomas are malignant cartilage-forming tumours representing around 20% of malignant primary tumours of bone and affect mainly adults in the third to sixth decade of life. Unfortunately, the molecular pathways controlling the genesis and the growth of chondrosarcoma cells are still not fully defined. It is well admitted that the invasion of bone by tumour cells affects the balance between early bone resorption and formation and induces an “inflammatory-like” environment which establishes a dialogue between tumour cells and their environment. The bone tumour microenvironment is then described as a sanctuary that contributes to the drug resistance patterns and may control at least in part the tumour growth. The concept of “niche” defined as a specialized microenvironment that can promote the emergence of tumour stem cells and provide all the required factors for their development recently emerges in the literature. The present paper aims to summarize the main evidence sustaining the existence of a specific bone niche in the pathogenesis of chondrosarcomas.