Distinct Biological Functions Research Articles

MSModDetector: A Tool for Detecting Mass Shifts and Post-Translational Modifications in Individual Ion Mass Spectrometry Data.

Post-translational modifications (PTMs) on proteins regulate protein structures and functions. A single protein molecule can possess multiple modification sites that can accommodate various PTM types, leading to a variety of different patterns, or combinations of PTMs, on that protein. Different PTM patterns can give rise to distinct biological functions. To facilitate the study of multiple PTMs on the same protein molecule, top-down mass spectrometry (MS) has proven to be a useful tool to measure the mass of intact proteins, thereby enabling even PTMs at distant sites to be assigned to the same protein molecule and allowing determination of how many PTMs are attached to a single protein. We developed a Python module called MSModDetector that studies PTM patterns from individual ion mass spectrometry (I2MS) data. I2MS is an intact protein mass spectrometry approach that generates true mass spectra without the need to infer charge states. The algorithm first detects and quantifies mass shifts for a protein of interest and subsequently infers potential PTM patterns using linear programming. The algorithm is evaluated on simulated I2MS data and experimental I2MS data for the tumor suppressor protein p53. We show that MSModDetector is a useful tool for comparing a protein's PTM pattern landscape across different conditions. An improved analysis of PTM patterns will enable a deeper understanding of PTM-regulated cellular processes. The source code is available at https://github.com/marjanfaizi/MSModDetector. Supplementary data are available at Bioinformatics online.

Enhancer selectivity across cell types delineates three functionally distinct enhancer-promoter regulation patterns

BackgroundMultiple enhancers co-regulating the same gene is prevalent and plays a crucial role during development and disease. However, how multiple enhancers coordinate the same gene expression across various cell types remains largely unexplored at genome scale.ResultsWe develop a computational approach that enables the quantitative assessment of enhancer specificity and selectivity across diverse cell types, leveraging enhancer-promoter (E-P) interactions data. We observe two well-known gene regulation patterns controlled by enhancer clusters, which regulate the same gene either in a limited number of cell types (Specific pattern, Spe) or in the majority of cell types (Conserved pattern, Con), both of which are enriched for super-enhancers (SEs). We identify a previously overlooked pattern (Variable pattern, Var) that multiple enhancers link to the same gene, but rarely coexist in the same cell type. These three patterns control the genes associating with distinct biological function and exhibit unique epigenetic features. Specifically, we discover a subset of Var patterns contains Shared enhancers with stable enhancer-promoter interactions in the majority of cell types, which might contribute to maintaining gene expression by recruiting abundant CTCF.ConclusionsTogether, our findings reveal three distinct E-P regulation patterns across different cell types, providing insights into deciphering the complexity of gene transcriptional regulation.

Identifying genes associated with disease outcomes using joint sparse canonical correlation analysis-An application in renal clear cell carcinoma.

Somatic changes like copy number aberrations (CNAs) and epigenetic alterations like methylation have pivotal effects on disease outcomes and prognosis in cancer, by regulating gene expressions, that drive critical biological processes. To identify potential biomarkers and molecular targets and understand how they impact disease outcomes, it is important to identify key groups of CNAs, the associated methylation, and the gene expressions they impact, through a joint integrative analysis. Here, we propose a novel analysis pipeline, the joint sparse canonical correlation analysis (jsCCA), an extension of sCCA, to effectively identify an ensemble of CNAs, methylation sites and gene (expression) components in the context of disease endpoints, especially tumor characteristics. Our approach detects potentially orthogonal gene components that are highly correlated with sets of methylation sites which in turn are correlated with sets of CNA sites. It then identifies the genes within these components that are associated with the outcome. Further, we aggregate the effect of each gene expression set on tumor stage by constructing "gene component scores" and test its interaction with traditional risk factors. Analyzing clinical and genomic data on 515 renal clear cell carcinoma (ccRCC) patients from the TCGA-KIRC, we found eight gene components to be associated with methylation sites, regulated by groups of proximally located CNA sites. Association analysis with tumor stage at diagnosis identified a novel association of expression of ASAH1 gene trans-regulated by methylation of several genes including SIX5 and by CNAs in the 10q25 region including TCF7L2. Further analysis to quantify the overall effect of gene sets on tumor stage, revealed that two of the eight gene components have significant interaction with smoking in relation to tumor stage. These gene components represent distinct biological functions including immune function, inflammatory responses, and hypoxia-regulated pathways. Our findings suggest that jsCCA analysis can identify interpretable and important genes, regulatory structures, and clinically consequential pathways. Such methods are warranted for comprehensive analysis of multimodal data especially in cancer genomics.

Endometrial Proliferative Phase-Centered View of Transcriptome Dynamics across the Menstrual Cycle.

The endometrium, the inner mucosal lining of the uterus, undergoes complex molecular and cellular changes across the menstrual cycle in preparation for embryo implantation. Transcriptome-wide analyses have mainly been utilized to study endometrial receptivity, the prerequisite for successful implantation, with most studies, so far, comparing the endometrial transcriptomes between (i) secretory and proliferative endometrium or (ii) mid-secretory and early secretory endometrium. In the current study, we provide a complete transcriptome description of the endometrium across the entire menstrual cycle and, for the first time, comprehensively characterize the proliferative phase of the endometrium. Our temporal transcriptome analysis includes five time points including the mid-proliferative, late proliferative (peri-ovulatory phase), early secretory, mid-secretory, and late secretory phases. Thus, we unveil exhaustively the transitions between the consecutive proliferative and secretory phases, highlighting their unique gene expression profiles and possible distinct biological functions. The transcriptome analysis reveals many differentially expressed genes (DEGs) across the menstrual cycle, most of which are phase-specific. As an example of coordinated gene activity, the expression profile of histone-encoding genes within the HIST cluster on chromosome 6 shows an increase in cluster activity during the late proliferative and a decline during the mid-secretory phase. Moreover, numerous DEGs are shared among all phases. In conclusion, in the current study, we delineate the endometrial proliferative phase-centered view of transcriptome dynamics across the menstrual cycle. Our data analysis highlights significant transcriptomic and functional changes occurring during the late proliferative phase-an essential transition point from the proliferative phase to the secretory phase. Future studies should explore how the biology of the late proliferative phase endometrium impacts the achievement of mid-secretory endometrial receptivity or contributes to molecular aberrations leading to embryo implantation failure.

A 3'-pre-tRNA-derived small RNA tRF-1-Ser regulated by 25(OH)D promotes proliferation and stemness by inhibiting the function of MBNL1 in breast cancer.

We explored the potential novel anticancer mechanisms of 25-hydroxyvitamin D (25(OH)D), a vitamin D metabolite with antitumour effects in breast cancer. It is stable in serum and is used to assess vitamin D levels in clinical practice. Transfer RNA-derived small RNAs are small noncoding RNAs that generate various distinct biological functions, but more research is needed on their role in breast cancer. Small RNA microarrays were used to explore the novel regulatory mechanism of 25(OH)D. High-throughput RNA-sequencing technology was used to detect transcriptome changes after 25(OH)D treatment and tRF-1-Ser knockdown. RNA pull-down and high-performance liquid chromatography-mass spectrometry/mass spectrometry were used to explore the proteins bound to tRF-1-Ser. In vitro and in vivo functional experiments were conducted to assess the influence of 25(OH)D and tRF-1-Ser on breast cancer. Semi-quantitative PCR was performed to detect alternative splicing events. Western blot assay and qPCR were used to assess protein and mRNA expression. The expression of tRF-1-Ser is negatively regulated by 25(OH)D. In our breast cancer (BRCA) clinical samples, we found that the expression of tRF-1-Ser was higher in cancer tissues than in paired normal tissues, and was significantly associated with tumour invasion. Moreover, tRF-1-Ser inhibits the function of MBNL1 by hindering its nuclear translocation. Functional experiments and transcriptome data revealed that the downregulation of tRF-1-Ser plays a vital role in the anticancer effect of 25(OH)D. In brief, our research revealed a novel anticancer mechanism of 25(OH)D, unveiled the vital function of tRF-1-Ser in BRCA progression, and suggested that tRF-1-Ser could emerge as a new therapeutic target for BRCA.

Androgen receptor splice variants drive castration-resistant prostate cancer metastasis by activating distinct transcriptional programs.

One critical mechanism through which prostate cancer (PCa) adapts to treatments targeting androgen receptor (AR) signaling is the emergence of ligand-binding domain-truncated and constitutively active AR splice variants, particularly AR-V7. While AR-V7 has been intensively studied, its ability to activate distinct biological functions compared to the full-length AR (AR-FL), and its role in regulating the metastatic progression of castration-resistant PCa (CRPC), remains unclear. Our study found that, under castrated conditions, AR-V7 strongly induced osteoblastic bone lesions, a response not observed with AR-FL overexpression. Through combined ChIP-seq, ATAC-seq, and RNA-seq analyses, we demonstrated that AR-V7 uniquely accesses the androgen-responsive elements in compact chromatin regions, activating a distinct transcription program. This program was highly enriched for genes involved in epithelial-mesenchymal transition and metastasis. Notably, we discovered that SOX9, a critical metastasis driver gene, was a direct target and downstream effector of AR-V7. Its protein expression was dramatically upregulated in AR-V7-induced bone lesions. Moreover, we found that Ser81 phosphorylation enhanced AR-V7's pro-metastasis function by selectively altering its specific transcription program. Blocking this phosphorylation with CDK9 inhibitors impaired the AR-V7-mediated metastasis program. Overall, our study has provided molecular insights into the role of AR splice variants in driving the metastatic progression of CRPC.

Site-Specific Analysis of Core and Antenna Fucosylation on Serum Glycoproteins.

Fucosylation is an important structural feature of glycans and plays an essential role in the regulation of glycoprotein functions. Fucosylation can be classified into core- (CF) and antenna-fucosylation (AF, also known as (sialyl-) Lewis) based on the location on N-glycans, and they perform distinct biological functions. In this study, core- and antenna-fucosylated N-glycans on human serum glycoproteins that hold great clinical application values were systematically characterized at the site-specific level using StrucGP combined with the recently developed fucosylation assignment method. The results showed that fucosylation was widely distributed on serum glycoproteins, with 50% of fucosylated glycopeptides modified by AF N-glycans, 37% by CF N-glycans, and 13% by dual-fucosylated N-glycans. Interestingly, CF and AF N-glycans preferred to modify different groups of serum glycoproteins with different tissue origins and were involved in distinctive biological processes. Specifically, AF N-glycoproteins are mainly from the liver and participated in complement activation, blood coagulation, and endopeptidase activities, while CF N-glycoproteins originate from diverse tissues and are mainly involved in cell adhesion and signaling transduction. These data further enhanced our understanding of fucosylation on circulation glycoproteins.

Neutrophils display distinct post-translational modifications in response to varied pathological stimuli

Neutrophils play a vital role in the innate immunity by perform effector functions through phagocytosis, degranulation, and forming extracellular traps. However, over-functioning of neutrophils has been associated with sterile inflammation such as Type 2 Diabetes, atherosclerosis, cancer and autoimmune disorders. Neutrophils exhibiting phenotypical and functional heterogeneity in both homeostatic and pathological conditions suggests distinct signaling pathways are activated in disease-specific stimuli and alter neutrophil functions. Hence, we examined mass spectrometry based post-translational modifications (PTM) of neutrophil proteins in response to pathologically significant stimuli, including high glucose, homocysteine and bacterial lipopolysaccharides representing diabetes-indicator, an activator of thrombosis and pathogen-associated molecule, respectively. Our data revealed that these aforesaid stimulators differentially deamidate, citrullinate, acetylate and methylate neutrophil proteins and align to distinct biological functions associated with degranulation, platelet activation, innate immune responses and metabolic alterations. The PTM patterns in response to high glucose showed an association with neutrophils extracellular traps (NETs) formation, homocysteine induced proteins PTM associated with signaling of systemic lupus erythematosus and lipopolysaccharides induced PTMs were involved in pathways related to cardiomyopathies. Our study provides novel insights into neutrophil PTM patterns and functions in response to varied pathological stimuli, which may serve as a resource to design therapeutic strategies for the management of neutrophil-centred diseases.

Application of Genetic Algorithms for Medical Diagnosis of Diabetes Mellitus

The system of glucose-insulin control and associated problems in diabetes mellitus were studied by mathematical modeling. It is a helpful theoretical tool for understanding the basic concepts of numerous distinct medical and biological functions. It delves into the various risk factors contributing to the onset of diabetes, such as sedentary lifestyle, obesity, family history, viruses, and increasing age. The study emphasizes the importance of mathematical models in understanding the dynamic characteristics of biological systems. The study emphasizes the increasing prevalence of diabetes, especially in India, where urbanization and lifestyle changes contribute to the rising incidence. The present investigation describes the use of John Holland's evolutionary computing approach and the Genetic Algorithm (GA) in diabetes mellitus. The Genetic Algorithm is applied to address issues related to diabetes, offering a generic solution and utilizing MATLAB's Genetic Algorithm tool. The Mathematical Model provides differential equations representing glucose and insulin concentrations in the blood. The results represent testing outcomes for normal, prediabetic, and diabetic individuals, optimized with Genetic Algorithm showcased through fitness value plots. The conclusion highlights the effectiveness of Genetic Algorithm as an optimization tool in predicting optimal samples for diabetes diagnosis. The paper encourages the use of heuristic algorithms, such as Genetic Algorithms, to address complex challenges in the field of diabetes research. Future scope includes further exploration of biomathematics and Genetic Algorithm applications for enhanced understanding and management of diabetes mellitus. It is critical for people with diabetes to consistently check their blood glucose levels and follow their treatment plan.

Single-cell integrative analysis reveals consensus cancer cell states and clinical relevance in breast cancer

High heterogeneity and complex interactions of malignant cells in breast cancer has been recognized as a driver of cancer progression and therapeutic failure. However, complete understanding of common cancer cell states and their underlying driver factors remain scarce and challenging. Here, we revealed seven consensus cancer cell states recurring cross patients by integrative analysis of single-cell RNA sequencing data of breast cancer. The distinct biological functions, the subtype-specific distribution, the potential cells of origin and the interrelation of consensus cancer cell states were systematically elucidated and validated in multiple independent datasets. We further uncovered the internal regulons and external cell components in tumor microenvironments, which contribute to the consensus cancer cell states. Using the state-specific signature, we also inferred the abundance of cells with each consensus cancer cell state by deconvolution of large breast cancer RNA-seq cohorts, revealing the association of immune-related state with better survival. Our study provides new insights for the cancer cell state composition and potential therapeutic strategies of breast cancer.

Abstract IA007: Tumor heterogeneity in ovarian clear cell carcinoma

Abstract IA007: Tumor heterogeneity in ovarian clear cell carcinoma

Single-cell RNA sequencing reveals the altered innate immunity in immune checkpoint inhibitor-related myocarditis.

Myocarditis has emerged as a rare but lethal immune checkpoint inhibitor (ICI)-associated toxicity. However, the exact mechanism and the specific therapeutic targets remain underexplored. In this study, we aim to characterise the transcriptomic profiles based on single-cell RNA sequencing from ICI-related myocarditis. Peripheral blood mononuclear cell (PBMC) samples were collected from four groups for single-cell RNA sequencing: (1) patients with newly diagnosed lung squamous cell carcinoma before treatment (Control Group); (2) patients with lung squamous cell carcinoma with PD-1 inhibitor therapy who did not develop myocarditis (PD-1 Group); (3) patients during fulminant ICI-related myocarditis onset (Myocarditis Group); and (4) Patients with fulminant ICI-related myocarditis during disease remission (Recovery Group). Subcluster determination, functional analysis, single-cell trajectory and cell-cell interaction analysis were performed after scRNA-seq. Bulk-RNA sequencing was performed for further validation. Our results revealed the diversity of cellular populations in ICI-related myocarditis, marked by their distinct transcriptional profiles and biological functions. Monocytes, NKs as well as B cells contribute to the regulation of innate immunity and inflammation in ICI-related myocarditis. With integrated analysis of scRNA-seq and bulk sequencing, we identified S100A protein family as a potential serum marker for ICI-related myocarditis. Our study has created a cell atlas of PBMC during ICI-related myocarditis, which would shed light on the pathophysiological mechanism and potential therapeutic targets of ICI-related myocarditis in continuous exploration.

Protein-intrinsic properties and context-dependent effects regulate pioneer factor binding and function.

Chromatin is a barrier to the binding of many transcription factors. By contrast, pioneer factors access nucleosomal targets and promote chromatin opening. Despite binding to target motifs in closed chromatin, many pioneer factors display cell-type-specific binding and activity. The mechanisms governing pioneer factor occupancy and the relationship between chromatin occupancy and opening remain unclear. We studied three Drosophila transcription factors with distinct DNA-binding domains and biological functions: Zelda, Grainy head and Twist. We demonstrated that the level of chromatin occupancy is a key determinant of pioneering activity. Multiple factors regulate occupancy, including motif content, local chromatin and protein concentration. Regions outside the DNA-binding domain are required for binding and chromatin opening. Our results show that pioneering activity is not a binary feature intrinsic to a protein but occurs on a spectrum and is regulated by a variety of protein-intrinsic and cell-type-specific features.

Identification of gut microbes-related molecular subtypes and their biomarkers in colorectal cancer.

The role of gut microbes (GM) and their metabolites in colorectal cancer (CRC) development has attracted increasing attention. Several studies have identified specific microorganisms that are closely associated with CRC occurrence and progression, as well as key genes associated with gut microorganisms. However, the extent to which gut microbes-related genes can serve as biomarkers for CRC progression or prognosis is still poorly understood. This study used a bioinformatics-based approach to synthetically analyze the large amount of available data stored in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Through this analysis, this study identified two distinct CRC molecular subtypes associated with GM, as well as CRC markers related to GM. In addition, these new subtypes exhibit significantly different survival outcomes and are characterized by distinct immune landscapes and biological functions. Gut microbes-related biomarkers (GMRBs), IL7 and BCL10, were identified and found to have independent prognostic value and predictability for immunotherapeutic response in CRC patients. In addition, a systematic collection and review of prior research literature on GM and CRC provided additional evidence to support these findings. In conclusion, this paper provides new insights into the underlying pathological mechanisms by which GM promotes the development of CRC and suggests potentially viable solutions for individualized prevention, screening, and treatment of CRC.

Machine learning and experiments revealed a novel pyroptosis-based classification linked to diagnosis and immune landscape in spinal cord injury

BackgroundRising evidence indicates the development of pyroptosis in the initiation and pathogenesis of spinal cord injury (SCI). However, the associated effects of pyroptosis-related genes (PRGs) in SCI are unclear. MethodsWe obtained the gene expression profiles of SCI and normal samples in the GEO. DatabaseThe R package limma screened for differentially expressed (DE) PRGs and performed functional enrichment analysis. Mechanical learning and PPI analysis helped filter essential PRGs to diagnose SCI. Peripheral blood was collected for validation from ten SCI patients and eight healthy individuals. The association of essential PRGs with immune infiltration was evaluated, and pyroptosis subtypes were recognized in SCI patients by unsupervised cluster analysis. Besides, a SCI model was built for in vivo validation of essential PRGs. ResultWe identified 25 DE-PRGs between SCI and normal controls. Functional enrichment analysis revealed the principal involvement of DE-PRGs in pyroptosis, inflammasome complex, interleukin-1 beta production, etc. Subsequently, three essential PRGs were identified and validated, showing excellent diagnostic efficacy and significant correlation with immune cell infiltration. Additionally, we developed diagnostic nomograms to predict the occurrence of SCI. Two pyroptosis subtypes exhibited distinct biological functions and immune landscapes among SCI patients. Finally, the expression of these essential PRGswas verified in vivo. ConclusionThe current study described the vital effects of pyroptosis-related genes in SCI, providing a novel direction for effective assessment and management of SCI.

Application of adipose-derived stem cells in ischemic heart disease: theory, potency, and advantage.

Adipose-derived mesenchymal stem cells (ASCs) represent an innovative candidate to treat ischemic heart disease (IHD) due to their abundance, renewable sources, minor invasiveness to obtain, and no ethical limitations. Compared with other mesenchymal stem cells, ASCs have demonstrated great advantages, especially in the commercialization of stem cell-based therapy. Mechanistically, ASCs exert a cardioprotective effect not only through differentiation into functional cells but also via robust paracrine of various bioactive factors that promote angiogenesis and immunomodulation. Exosomes from ASCs also play an indispensable role in this process. However, due to the distinct biological functions of ASCs from different origins or donors with varing health statuses (such as aging, diabetes, or atherosclerosis), the heterogeneity of ASCs deserves more attention. This prompts scientists to select optimal donors for clinical applications. In addition, to overcome the primary obstacle of poor retention and low survival after transplantation, a variety of studies have been dedicated to the engineering of ASCs with biomaterials. Besides, clinical trials have confirmed the safety and efficacy of ASCs therapy in the context of heart failure or myocardial infarction. This article reviews the theory, efficacy, and advantages of ASCs-based therapy, the factors affecting ASCs function, heterogeneity, engineering strategies and clinical application of ASCs.

Immune-related transcriptomic and epigenetic reconfiguration in BV2 cells after lipopolysaccharide exposure: an in vitro omics integrative study.

Molecular alterations affecting microglia have been consistently associated with the inflammatory response. These cells can have pro- or anti-inflammatory activity, phenotypes thought to be regulated by epigenetic mechanisms. Still, little is known about the details on how epigenetic marks regulate the expression of genes in the context of an inflammatory response. Through CUT&RUN, we profiled four genome-wide histone marks (HM) (H3K4me1, H3K4me3, H3K27ac, and H3K27me3) in lipopolysaccharide-exposed cells and compared their distributions to control cells. Transcriptomic profiles were determined through RNA-seq and differentially expressed genes were identified and contrasted with the epigenetic landscapes. Other downstream analyses were also included in this study. Our results illustrate an effectively induced M1 phenotype in microglial cells derived from LPS exposure. We observed differential bound regions associated with the genes classically involved in the inflammatory response in the expected direction according to each histone modification. Consistently, our transcriptomic analysis yielded a conspicuous illustration of the LPS-induced immune activity showing the up-regulation of Nf-κB-induced mRNAs (TNF-α, nfκbiz, nfκbia) and other important genes (Marco, Il-6, etc.). Furthermore, we integrated both omics profiles and identified an important reconfiguration of the genome induced by LPS. The latter was depicted by 8 different chromatin states that changed between conditions and that associated with unique clusters of differentially expressed genes, which not only represented regulatory elements, but also underlined distinct biological functions (inhibition of morphogenesis; changes in metabolism, homeostasis, and cytokine regulation; activation of the inflammatory response). This study exhibits important differences in the distribution of histone modifications in treated and control BV2 cells, constituting an epigenetic reconfiguration that leads to the inflammatory response. Also, it highlights the importance of these marks' regulatory role in gene expression and provides possible targets for further studies in the context of inflammation.

The Staphylococcus aureus CamS lipoprotein is a repressor of toxin production that shapes host-pathogen interaction.

Lipoproteins of the opportunistic pathogen Staphylococcus aureus play a crucial role in various cellular processes and host interactions. Consisting of a protein and a lipid moiety, they support nutrient acquisition and anchor the protein to the bacterial membrane. Recently, we identified several processed and secreted small linear peptides that derive from the secretion signal sequence of S. aureus lipoproteins. Here, we show, for the first time, that the protein moiety of the S. aureus lipoprotein CamS has a biological role that is distinct from its associated linear peptide staph-cAM373. The small peptide was shown to be involved in interspecies horizontal gene transfer, the primary mechanism for the dissemination of antibiotic resistance among bacteria. We provide evidence that the CamS protein moiety is a potent repressor of cytotoxins, such as α-toxin and leukocidins. The CamS-mediated suppression of toxin transcription was reflected by altered disease severity in in vivo infection models involving skin and soft tissue, as well as bloodstream infections. Collectively, we have uncovered the role of the protein moiety of the staphylococcal lipoprotein CamS as a previously uncharacterized repressor of S. aureus toxin production, which consequently regulates virulence and disease outcomes. Notably, the camS gene is conserved in S. aureus, and we also demonstrated the muted transcriptional response of cytotoxins in 2 different S. aureus lineages. Our findings provide the first evidence of distinct biological functions of the protein moiety and its associated linear peptide for a specific lipoprotein. Therefore, lipoproteins in S. aureus consist of 3 functional components: a lipid moiety, a protein moiety, and a small linear peptide, with putative different biological roles that might not only determine the outcome of host-pathogen interactions but also drive the acquisition of antibiotic resistance determinants.

Anoikis-related signature identifies tumor microenvironment landscape and predicts prognosis and drug sensitivity in colorectal cancer.

Background: Anoikis, a mechanism of programmed apoptosis, plays an important role in growth and metastasis of tumors. However, there are still few available comprehensive reports on the impact of anoikis on colorectal cancer. Method: A clustering analysis was done on 133 anoikis-related genes in GSE39582, and we compared clinical features between clusters, the tumor microenvironment was analyzed with algorithms such as "Cibersort" and "ssGSEA". We investigated risk scores of clinical feature groups and anoikis-associated gene mutations after creating a predictive model. We incorporated clinical traits to build a nomogram. Additionally, the quantitative real-time PCR was employed to investigate the mRNA expression of selected anoikis-associated genes. Result: We identified two anoikis-related clusters with distinct prognoses, clinical characteristics, and biological functions. One of the clusters was associated with anoikis resistance, which activated multiple pathways encouraging tumor metastasis. In our prognostic model, oxaliplatin may be a sensitive drug for low-risk patients. The nomogram showed good ability to predict survival time. And SIRT3, PIK3CA, ITGA3, DAPK1, and CASP3 increased in CRC group through the PCR assay. Conclusion: Our study identified two distinct modes of anoikis in colorectal cancer, with active metastasis-promoting pathways inducing an anti-anoikis subtype, which has a stronger propensity for metastasis and a worse prognosis than an anoikis-activated subtype. Massive immune cell infiltration may be an indicator of anoikis resistance. Anoikis' role in the colorectal cancer remains to be investigated.

Size matters: Functional differences of small extracellular vesicle subpopulations in cardiac repair responses.

Cardiac progenitor cell (CPC)-derived small extracellular vesicles (sEVs) exhibit great potential to stimulate cardiac repair. However, the multifaceted nature of sEV heterogeneity presents a challenge in understanding the distinct mechanisms underlying their regenerative abilities. Here, a dual-step multimodal flowthrough and size-exclusion chromatography method was applied to isolate and separate CPC-derived sEV subpopulations to study the functional differences related to cardiac repair responses. Three distinct sEV subpopulations were identified with unique protein profiles. Functional cell assays for cardiac repair-related processes demonstrated that the middle-sized and smallest-sized sEV subpopulations exhibited the highest pro-angiogenic and anti-fibrotic activities. Proteasome activity was uniquely seen in the smallest-sized subpopulation. The largest-sized subpopulation showed no effect in any of the functional assays. This research uncovers the existence of sEV subpopulations, each characterized by a distinct composition and biological function. Enhancing our understanding of sEV heterogeneity will provide valuable insights into sEV mechanisms of action, ultimately accelerating the translation of sEV therapeutics.