The Integrative Analysis of Thrombospondin Family Genes in Pan-Cancer Reveals that THBS2 Facilitates Gastrointestinal Cancer Metastasis

Integrating bulk RNA-seq and scRNA-seq analyses revealed the function and clinical value of thrombospondins in colon cancer

Background

Acting as mediators in cell-matrix and cell-cell communication, matricellular proteins play a crucial role in cancer progression. Thrombospondins (TSPs), a type of matricellular glycoproteins, are key regulators in cancer biology with multifaceted roles. Although TSPs have been implicated in anti-tumor immunity and epithelial-mesenchymal transition (EMT) in several malignancies, their specific roles to colon cancer remain elusive. Addressing this knowledge gap is essential, as understanding the function of TSPs in colon cancer could identify new therapeutic targets and prognostic markers.

Methods

Analyzing 1981 samples from 10 high-throughput datasets, including six bulk RNA-seq, three scRNA-seq, and one spatial transcriptome dataset, our study investigated the prognostic relevance, risk stratification value, immune heterogeneity, and cellular origin of TSPs, as well as their influence on cancer-associated fibroblasts (CAFs). Utilizing survival analysis, unsupervised clustering, and functional enrichment, along with multiple correlation analyses of the tumor-microenvironment (TME) via Gene Set Variation Analysis (GSVA), spatial localization, Monocle2, and CellPhoneDB, we provided insights into the clinical and cellular implications of TSPs.

Results

First, we observed significant upregulation of THBS2 and COMP in colon cancer, both of which displayed significant prognostic value. Additionally, we detected a significant positive correlation between TSPs and immune cells, as well as marker genes of EMT. Second, based on TSPs expression, patients were divided into two clusters with distinct prognoses: the high TSPs expression group (TSPs-H) was characterized by pronounced immune and stromal cell infiltration, and notably elevated T-cell exhaustion scores. Subsequently, we found that THBS2 and COMP may be associated with the differentiation of CAFs into pan-iCAFs and pan-dCAFs, which are known for their heightened matrix remodeling activities. Moreover, THBS2 enhanced CAFs communication with vascular endothelial cells and monocyte-macrophages. CAFs expressing THBS2 (THBS2+ CAFs) demonstrated higher scores across multiple signaling pathways, including angiogenic, EMT, Hedgehog, Notch, Wnt, and TGF-β, when compared to THBS2- CAFs. These observations suggest that THBS2 may be associated with stronger pro-carcinogenic activity in CAFs.

Conclusions

This study revealed the crucial role of TSPs and the significant correlation between THBS2 and CAFs interactions in colon cancer progression, providing valuable insights for targeting TSPs to mitigate cancer progression.

Machine learning-based model for CD4+ conventional T cell genes to predict survival and immune responses in colorectal cancer

Globally, CRC ranks as a principal cause of mortality, with projections indicating a substantial rise in both incidence and mortality by the year 2040. The immunological responses to cancer heavily rely on the function of CD4Tconv. Despite this critical role, prognostic studies on CRC-related CD4Tconv remain insufficient. In this investigation, transcriptomic and clinical data were sourced from TCGA and GEO. Initially, we pinpointed CD4TGs using single-cell datasets. Prognostic genes were then isolated through univariate Cox regression analysis. Building upon this, 101 machine learning algorithms were employed to devise a novel risk assessment framework, which underwent rigorous validation using Kaplan-Meier survival analysis, univariate and multivariate Cox regression, time-dependent ROC curves, nomograms, and calibration plots. Furthermore, GSEA facilitated the examination of these genes' potential roles. The RS derived from this model was also analyzed for its implications in the TME, and its potential utility in immunotherapy and chemotherapy contexts. A novel prognostic model was developed, utilizing eight CD4TGs that are significantly linked to the outcomes of patients with CRC. This model's RS showcased remarkable predictive reliability for the overall survival rates of CRC patients and strongly correlated with malignancy levels. RS serves as an autonomous prognostic indicator, capable of accurately forecasting patient prognoses. Based on the median value of RS, patients were categorized into subgroups of high and low risk. The subgroup with higher risk demonstrated increased immune infiltration and heightened activity of genes associated with immunity. This investigation's establishment of a CD4TGs risk model introduces novel biomarkers for the clinical evaluation of CRC risks. These biomarkers may enhance therapeutic approaches and, in turn, elevate the clinical outcomes for patients with CRC by facilitating an integrated treatment strategy.

NetMIM: network-based multi-omics integration with block missingness for biomarker selection and disease outcome prediction

Compared with analyzing omics data from a single platform, an integrative analysis of multi-omics data provides a more comprehensive understanding of the regulatory relationships among biological features associated with complex diseases. However, most existing frameworks for integrative analysis overlook two crucial aspects of multi-omics data. Firstly, they neglect the known dependencies among biological features that exist in highly credible biological databases. Secondly, most existing integrative frameworks just simply remove the subjects without full omics data to handle block missingness, resulting in decreasing statistical power. To overcome these issues, we propose a network-based integrative Bayesian framework for biomarker selection and disease outcome prediction based on multi-omics data. Our framework utilizes Dirac spike-and-slab variable selection prior to identifying a small subset of biomarkers. The incorporation of gene pathway information improves the interpretability of feature selection. Furthermore, with the strategy in the FBM (stand for "full Bayesian model with missingness") model where missing omics data are augmented via a mechanistic model, our framework handles block missingness in multi-omics data via a data augmentation approach. The real application illustrates that our approach, which incorporates existing gene pathway information and includes subjects without DNA methylation data, results in more interpretable feature selection results and more accurate predictions.

Decellularized Antler Cancellous Bone Matrix Material Can Serve as Potential Bone Tissue Scaffold

Due to the limited supply of autologous bone grafts, there is a need to develop more bone matrix materials to repair bone defects. Xenograft bone is expected to be used for clinical treatment due to its exact structural similarity to natural bone and its high biocompatibility. In this study, decellularized antler cancellous bone matrix (DACB) was first prepared, and then the extent of decellularization of DACB was verified by histological staining, which demonstrated that it retained the extracellular matrix (ECM). The bioactivity of DACB was assessed using C3H10T1/2 cells, revealing that DACB enhanced cell proliferation and facilitated cell adhesion and osteogenic differentiation. When evaluated by implanting DACB into nude mice, there were no signs of necrosis or inflammation in the epidermal tissues. The bone repair effect of DACB was verified in vivo using sika deer during the antler growth period as an animal model, and the molecular mechanisms of bone repair were further evaluated by transcriptomic analysis of the regenerated tissues. Our findings suggest that the low immunogenicity of DACB enhances the production of bone extracellular matrix components, leading to effective osseointegration between bone and DACB. This study provides a new reference for solving bone defects.

Infiltrative pattern of invasion is independently associated with shorter survival and desmoplastic stroma markers FAP and THBS2 in mucinous ovarian carcinoma

AIMS

Mucinous ovarian carcinoma (MOC) is a rare ovarian cancer histotype with generally good prognosis when diagnosed at an early stage. However, MOC with the infiltrative pattern of invasion has a worse prognosis, although to date studies have not been large enough to control for covariables. Data on reproducibility of classifying the invasion pattern are limited, as are molecular correlates for infiltrative invasion. We hypothesized that the invasion pattern would be associated with an aberrant tumour microenvironment.

METHODS AND RESULTS

Four subspecialty pathologists assessed interobserver reproducibility of the pattern of invasion in 134 MOC. Immunohistochemistry on fibroblast activation protein (FAP) and THBS2 was performed on 98 cases. Association with survival was tested using Cox regression. The average interobserver agreement for the infiltrative pattern was moderate (kappa 0.60, agreement 86.3%). After reproducibility review, 24/134 MOC (18%) were determined to have the infiltrative pattern and this was associated with a higher risk of death, independent of FIGO stage, grade, and patient age in a time-dependent manner (hazard ratio [HR] = 10.2, 95% confidence interval [CI] 3.0-34.5). High stromal expression of FAP and THBS2 was more common in infiltrative MOC (FAP: 60%, THBS2: 58%, both P < 0.001) and associated with survival (multivariate HR for FAP: 1.5 [95% CI 1.1-2.1] and THBS2: 1.91 [95% CI 1.1-3.2]).

CONCLUSIONS

The pattern of invasion should be included in reporting for MOC due to the strong prognostic implications. We highlight the histological features that should be considered to improve reproducibility. FAP and THBS2 are associated with infiltrative invasion in MOC.

A large-scale genome-wide cross-trait analysis for the effect of COVID-19 on female-specific cancers

Little is known regarding the long-term adverse effects of COVID-19 on female-specific cancers, nor the shared genetic influences underlying these conditions. We performed a comprehensive genome-wide cross-trait analysis to investigate the shared genetic architecture between COVID-19 (infection, hospitalization, and critical illness) with three female-specific cancers (breast cancer (BC), epithelial ovarian cancer (EOC), and endometrial cancer (EC)). We identified significant genome-wide genetic correlations with EC for both hospitalization (r g  = 0.19, p = 0.01) and critical illness (r g  = 0.29, p = 3.00 × 10-4). Mendelian randomization demonstrated no valid association of COVID-19 with any cancer of interest, except for suggestive associations of genetically predicted hospitalization (ORIVW = 1.09, p = 0.04) and critical illness (ORIVW = 1.06, p = 0.04) with EC risk, none withstanding multiple correction. Cross-trait meta-analysis identified 20 SNPs shared between COVID-19 with BC, 15 with EOC, and 5 with EC; and transcriptome-wide association studies revealed multiple shared genes. Findings support intrinsic links underlying these complex traits, highlighting shared mechanisms rather than causal associations.

Activation of ACLY by SEC63 deploys metabolic reprogramming to facilitate hepatocellular carcinoma metastasis upon endoplasmic reticulum stress

BACKGROUND

Tumor cells display augmented capability to maintain endoplasmic reticulum (ER) homeostasis and hijack ER stress pathway for malignant phenotypes under microenvironmental stimuli. Metabolic reprogramming is a well-known hallmark for tumor cells to provide specific adaptive traits to the microenvironmental alterations. However, it's unknown how tumor cells orchestrate metabolic reprogramming and tumor progression in response to ER stress. Herein, we aimed to explore the pivotal roles of SEC63-mediated metabolic remodeling in hepatocellular carcinoma (HCC) cell metastasis after ER stress.

METHODS

The expression levels of SEC63 in HCC tissues and adjacent non-cancerous tissues were determined by immunohistochemistry and western blot. The regulatory roles of SEC63 in HCC metastasis were investigated both in vitro and in vivo by RNA-sequencing, metabolites detection, immunofluorescence, and transwell migration/invasion analyses. GST pull-down, immunoprecipitation/mass spectrometry and in vivo ubiquitination/phosphorylation assay were conducted to elucidate the underlying molecular mechanisms.

RESULTS

We identified SEC63 as a new regulator of HCC cell metabolism. Upon ER stress, the phosphorylation of SEC63 at T537 by IRE1α pathway contributed to SEC63 activation. Then, the stability of ACLY was upregulated by SEC63 to increase the supply of acetyl-CoA and lipid biosynthesis, which are beneficial for improving ER capacity. Meanwhile, SEC63 also entered into nucleus for increasing nuclear acetyl-CoA production to upregulate unfolded protein response targets to improve ER homeostasis. Importantly, SEC63 coordinated with ACLY to epigenetically modulate expression of Snail1 in the nucleus. Consequently, SEC63 promoted HCC cell metastasis and these effects were reversed by ACLY inhibition. Clinically, SEC63 expression was significantly upregulated in HCC tissue specimens and was positively correlated with ACLY expression. Importantly, high expression of SEC63 predicted unfavorable prognosis of HCC patients.

CONCLUSIONS

Our findings revealed that SEC63-mediated metabolic reprogramming plays important roles in keeping ER homeostasis upon stimuli in HCC cells. Meanwhile, SEC63 coordinates with ACLY to upregulate the expression of Snail1, which further promotes HCC metastasis. Metastasis is crucial for helping cancer cells seek new settlements upon microenvironmental stimuli. Taken together, our findings highlight a cancer selective adaption to ER stress as well as reveal the potential roles of the IRE1α-SEC63-ACLY axis in HCC treatment.

Whole-exome mutational landscape and molecular marker study in mucinous and clear cell ovarian cancer cell lines 3AO and ES2

BACKGROUND

Ovarian cancer is one of the most lethal cancers in women because it is often diagnosed at an advanced stage. The molecular markers investigated thus far have been unsatisfactory.

METHODS

We performed whole-exome sequencing on the human ovarian cancer cell lines 3AO and ES2 and the normal ovarian epithelial cell line IOSE-80. Molecular markers of ovarian cancer were screened from shared mutation genes and copy number variation genes in the 6q21-qter region.

RESULTS

We found that missense mutations were the most common mutations in the gene (93%). The MUC12, FLG and MUC16 genes were highly mutated in 3AO and ES2 cells. Copy number amplification occurred mainly in 4p16.1 and 11q14.3, and copy number deletions occurred in 4q34.3 and 18p11.21. A total of 23 hub genes were screened, of which 16 were closely related to the survival of ovarian cancer patients. The three genes CCDC170, THBS2 and COL14A1 are most significantly correlated with the survival and prognosis of ovarian cancer. In particular, the overall survival of ovarian cancer patients with high CCDC170 gene expression was significantly prolonged (P < 0.001). The expression of CCDC170 in normal tissues was significantly higher than that in ovarian cancer tissues (P < 0.05), and its expression was significantly decreased in advanced ovarian cancer. Western blotting and immunofluorescence assays also showed that the expression of CCDC170 in ovarian cancer cells was significantly lower than that in normal cells (P < 0.001, P < 0.01).

CONCLUSIONS

CCDC170 is expected to become a new diagnostic molecular target and prognostic indicator for ovarian cancer patients, which can provide new ideas for the design of antitumor drugs.

Controlled extracellular proteolysis of thrombospondins

Limited proteolysis of thrombospondins is a powerful mechanism to ensure dynamic tuning of their activities in the extracellular space. Thrombospondins are multifunctional matricellular proteins composed of multiple domains, each with a specific pattern of interactions with cell receptors, matrix components and soluble factors (growth factors, cytokines and proteases), thus with different effects on cell behavior and responses to changes in the microenvironment. Therefore, the proteolytic degradation of thrombospondins has multiple functional consequences, reflecting the local release of active fragments and isolated domains, exposure or disruption of active sequences, altered protein location, and changes in the composition and function of TSP-based pericellular interaction networks. In this review current data from the literature and databases is employed to provide an overview of cleavage of mammalian thrombospondins by different proteases. The roles of the fragments generated in specific pathological settings, with particular focus on cancer and the tumor microenvironment, are discussed.

Identification of THSD7B and PRMT9 mutations as risk factors for familial lung adenocarcinoma: A case report

RATIONALE

Lung tumors arise from the unrestrained malignant growth of pulmonary epithelial cells. Lung cancer cases include both small and non-small cell lung cancers, with lung adenocarcinoma (LUAD) accounting for roughly half of all non-small cell lung cancer cases. Research focused on familial cancers suggests that approximately 8% of lung cancer cases are linked to genetic susceptibility or heritability. The precise genetic factors that underlie the onset of lung cancer, however, remain to be firmly established.

PATIENT CONCERNS

A 43-year-old presented with nodules in the lower left lung lobe. Following initial antibiotic treatment in a local hospital, these nodules remained present and the patient subsequently underwent the resection of the left lower lobe of the lung. The patient also had 4 family members with a history of LUAD.

DIAGNOSIS

Immunohistochemical staining results including cytokeratin 7 (+), TTF-1 (+), new aspartic proteinase A (+), CK5/6 (-), P63 (-), and Ki-67 (5%+) were consistent with a diagnosis of LUAD.

INTERVENTION

Whole exome sequencing analyses of 5 patients and 6 healthy family members were performed to explore potential mutations associated with familial LUAD.

OUTCOMES

Whole exome sequencing was conducted, confirming that the proband and their 4 other family members with LUAD harbored heterozygous THSD7B (c.A4000G:p.S1334G) mutations and homozygous PRMT9 (c.G40T:p.G14C) mutations, as further confirmed via Sanger sequencing. These mutations were predicted to be deleterious using the SIFT, PolyPhen2, and MutationTaster algorithms. Protein structure analyses indicated that the mutation of the serine at amino acid position 1334 in THSD7B to a glycine would reduce the minimum free energy from 8.08 kcal/mol to 68.57 kcal/mol. The identified mutation in the PRMT9 mutation was not present in the predicted protein structure. I-Mutant2.0 predictions indicated that both of these mutations (THSD7B:p.S1334G and PRMT9: p.G14C) were predicted to reduce protein stability.

LESSONS

Heterozygous THSD7B (c.A4000G:p.S1334G) and the homozygous PRMT9 (c.G40T:p.G14C) mutations were found to be linked to LUAD incidence in the analyzed family. Early analyses of these genetic loci and timely genetic counseling may provide benefits and aid in the early diagnosis of familial LUAD.

Patient-derived xenograft model in colorectal cancer basic and translational research

Colorectal cancer (CRC) is one of the most popular malignancies globally, with 930 000 deaths in 2020. The evaluation of CRC-related pathogenesis and the discovery of potential therapeutic targets will be meaningful and helpful for improving CRC treatment. With huge efforts made in past decades, the systematic treatment regimens have been applied to improve the prognosis of CRC patients. However, the sensitivity of CRC to chemotherapy and targeted therapy is different from person to person, which is an important cause of treatment failure. The emergence of patient-derived xenograft (PDX) models shows great potential to alleviate the straits. PDX models possess similar genetic and pathological characteristics as the features of primary tumors. Moreover, PDX has the ability to mimic the tumor microenvironment of the original tumor. Thus, the PDX model is an important tool to screen precise drugs for individualized treatment, seek predictive biomarkers for prognosis supervision, and evaluate the unknown mechanism in basic research. This paper reviews the recent advances in constructed methods and applications of the CRC PDX model, aiming to provide new knowledge for CRC basic research and therapeutics.

MNRR1 is a driver of ovarian cancer progression

Cancer progression requires the acquisition of mechanisms that support proliferative potential and metastatic capacity. MNRR1 (also CHCHD2, PARK22, AAG10) is a bi-organellar protein that in the mitochondria can bind to Bcl-xL to enhance its anti-apoptotic function, or to respiratory chain complex IV (COX IV) to increase mitochondrial respiration. In the nucleus, it can act as a transcription factor and promote the expression of genes involved in mitochondrial biogenesis, migration, and cellular stress response. Given that MNRR1 can regulate both apoptosis and mitochondrial respiration, as well as migration, we hypothesize that it can modulate metastatic spread. Using ovarian cancer models, we show heterogeneous protein expression levels of MNRR1 across samples tested and cell-dependent control of its stability and binding partners. In addition to its anti-apoptotic and bioenergetic functions, MNRR1 is both necessary and sufficient for a focal adhesion and ECM repertoire that can support spheroid formation. Its ectopic expression is sufficient to induce the adhesive glycoprotein THBS4 and the type 1 collagen, COL1A1. Conversely, its deletion leads to significant downregulation of these genes. Furthermore, loss of MNRR1 leads to delay in tumor growth, curtailed carcinomatosis, and improved survival in a syngeneic ovarian cancer mouse model. These results suggest targeting MNRR1 may improve survival in ovarian cancer patients.

Matricellular proteins in cutaneous wound healing

Cutaneous wound healing is a complex process that encompasses alterations in all aspects of the skin including the extracellular matrix (ECM). ECM consist of large structural proteins such as collagens and elastin as well as smaller proteins with mainly regulative properties called matricellular proteins. Matricellular proteins bind to structural proteins and their functions include but are not limited to interaction with cell surface receptors, cytokines, or protease and evoking a cellular response. The signaling initiated by matricellular proteins modulates differentiation and proliferation of cells having an impact on the tissue regeneration. In this review we give an overview of the matricellular proteins that have been found to be involved in cutaneous wound healing and summarize the information known to date about their functions in this process.

The Systematic Analyses of RING Finger Gene Signature for Predicting the Prognosis of Patients with Hepatocellular Carcinoma

RING finger (RNF) proteins are frequently dysregulated in human malignancies and are tightly associated with tumorigenesis. However, the expression profiles of RNF genes in hepatocellular carcinoma (HCC) and their relations with prognosis remain undetermined. Here, we aimed at constructing a prognostic model according to RNF genes for forecasting the outcomes of HCC patients using the data from The Cancer Genome Atlas (TCGA) program. We collected HCC datasets to validate the values of our model in predicting prognosis of HCC patients from International Cancer Genome Consortium (ICGC) platform. Then, functional experiments were carried out to explore the roles of the representative RNF in HCC progression. A total of 107 differentially expressed RNFs were obtained between TCGA-HCC tumor and normal tissues. After comprehensive evaluation, a prognostic signature composed of 11 RNFs (RNF220, RNF25, TRIM25, BMI1, RNF216P1, RNF115, RNF2, TRAIP, RNF157, RNF145, and RNF19B) was constructed based on TCGA cohort. Then, the Kaplan-Meier (KM) curves and the receiver operating characteristic curve (ROC) were employed to evaluate predictive power of the prognostic model in testing cohort (TCGA) and validation cohort (ICGC). The KM and ROC curves illustrated the good predictive power in testing and validation cohort. The areas under the ROC curve are 0.77 and 0.76 in these two cohorts, respectively. Among the prognostic signature genes, BMI1 was selected as a representative for functional study. We found that BMI1 protein level was significantly upregulated in HCC tissues. Moreover, the inhibitor of BMI1, PTC-209, displayed an excellent anti-HCC effect in vitro. Enrichment analysis of BMI1 downstream targets showed that BMI1 might be involved in tumor immunotherapy. Together, our overall analyses revealed that the 11-RNFs prognostic signature might provide us latent chances for evaluating HCC prognosis and developing novel HCC therapy.

The Dysregulation of SOX Family Correlates with DNA Methylation and Immune Microenvironment Characteristics to Predict Prognosis in Hepatocellular Carcinoma

Background

Due to the molecular heterogeneity of hepatocellular carcinoma (HCC), majority of patients respond poorly among various of therapy. This study is aimed at conducting a comprehensive analysis about roles of SOX family in HCC for obtaining more therapeutic targets and biomarkers which may bring new ideas for the treatment of HCC.

Methods

UALCAN, Kaplan Meier plotter, cBioPortal, STRING, WebGestalt, Metascape, TIMER 2.0, DiseaseMeth, MethSurv, HPA, CCLE database, and Cytoscape software were used to comprehensively analyze the bioinformatic data.

Results

SOX2, SOX4, SOX8, SOX10, SOX11, SOX12, SOX17, and SOX18 were significantly differentially expressed in HCC and normal tissues and were valuable for the grade and survival of HCC patients. In addition, the gene alterations of SOX family happened frequently, and SOX4 and SOX17 had the highest mutation rate. The function of SOX family on HCC may be closely correlated with the regulation of angiogenesis-related signaling pathways. Moreover, SOX4, SOX8, SOX11, SOX12, SOX17, and SOX18 were correlation with 8 types of immune cells (including CD8+ T cell, CD4+ T cell, B cell, Tregs, neutrophil, macrophage, myeloid DC, and NK cell), and we found that most types of immune cells had a positive correlation with SOX family. Notably, CD4+ T cell and macrophage were positively related with all these SOX family. NK cells were negatively related with most SOX family genes. DNA methylation levels in promoter area of SOX2, SOX4, and SOX10 were lower in HCC than normal tissues, while SOX8, SOX11, SOX17, and SOX18 had higher DNA methylation levels than normal tissues. Moreover, higher DNA methylation level of SOX12 and SOX18 demonstrated worse survival rates in patients with HCC.

Conclusion

SOX family genes could predict the prognosis of HCC. In addition, the regulation of angiogenesis-related signaling pathways may participate in the development of HCC. DNA methylation level and immune microenvironment characteristics (especially CD4+ T cell and macrophage immune cell infiltration) could be a novel insight for predicting prognosis in HCC.