High copy number variations, particular transcription factors, and low immunity contribute to the stemness of prostate cancer cells

Putative Dual Roles of Bone Morphogenetic Protein 8B (BMP8B) in Disease Progression of Gastric Cancer

Background/Aim

Increased expression of bone morphogenetic protein 8B (BMP8B) in bone marrow and primary tumors of patients with gastric cancer (GC) is associated with disease progression and poor prognosis. However, a reduced expression has also been seen in GCs due to histone acetylation. This study aimed to evaluate BMP8B transcript levels in a large GC cohort and its impact on cellular functions.

Materials and Methods

BMP8B transcripts were determined in 319 gastric tumors and compared with 182 adjacent normal tissues using real time PCR, with a further analysis conducted in the TCGA database. Kaplan-Meier plotter analysis was performed to evaluate the correlation between BMP8B and prognosis of the disease. BMP8B knockdown model was employed to determine the effect of BMP8B on the function of GC cells (HGC27).

Results

BMP8B mRNA levels were significantly up-regulated in the GC tissues compared with adjacent normal tissues in both TCGA database and our own database from Beijing Cancer Hospital, and high BMP8B expression was associated with poor prognosis. BMP8B is most likely to be involved in the differentiation of GC. Poorly differentiated GC samples presented a significantly reduced BMP8B expression in relation to well-differentiated and moderately differentiated GC. BMP8B knockdown inhibited proliferation of GC cells, while promoted invasion and migration of cancer cells.

Conclusion

BMP8B was reduced in GCs, whereas higher BMP8B expression was associated with poor prognosis. BMP8B knockdown inhibited proliferation of GC cells, and promoted invasion and migration. Our results suggest that BMP8B plays dual roles in GC.

Comprehensive data mining reveals RTK/RAS signaling pathway as a promoter of prostate cancer lineage plasticity through transcription factors and CNV

Prostate cancer lineage plasticity is a key driver in the transition to neuroendocrine prostate cancer (NEPC), and the RTK/RAS signaling pathway is a well-established cancer pathway. Nevertheless, the comprehensive link between the RTK/RAS signaling pathway and lineage plasticity has received limited investigation. In particular, the intricate regulatory network governing the interplay between RTK/RAS and lineage plasticity remains largely unexplored. The multi-omics data were clustered with the coefficient of argument and neighbor joining algorithm. Subsequently, the clustered results were analyzed utilizing the GSEA, gene sets related to stemness, multi-lineage state datasets, and canonical cancer pathway gene sets. Finally, a comprehensive exploration of the data based on the ssGSEA, WGCNA, GSEA, VIPER, prostate cancer scRNA-seq data, and the GPSAdb database was conducted. Among the six modules in the clustering results, there are 300 overlapping genes, including 3 previously unreported prostate cancer genes that were validated to be upregulated in prostate cancer through RT-qPCR. Function Module 6 shows a positive correlation with prostate cancer cell stemness, multi-lineage states, and the RTK/RAS signaling pathway. Additionally, the 19 leading-edge genes of the RTK/RAS signaling pathway promote prostate cancer lineage plasticity through a complex network of transcriptional regulation and copy number variations. In the transcriptional regulation network, TP63 and FOXO1 act as suppressors of prostate cancer lineage plasticity, whereas RORC exerts a promoting effect. This study provides a comprehensive perspective on the role of the RTK/RAS pathway in prostate cancer lineage plasticity and offers new clues for the treatment of NEPC.

A statistical learning method for simultaneous copy number estimation and subclone clustering with single-cell sequencing data

The availability of single-cell sequencing (SCS) enables us to assess intra-tumor heterogeneity and identify cellular subclones without the confounding effect of mixed cells. Copy number aberrations (CNAs) have been commonly used to identify subclones in SCS data using various clustering methods, as cells comprising a subpopulation are found to share a genetic profile. However, currently available methods may generate spurious results (e.g., falsely identified variants) in the procedure of CNA detection, thereby diminishing the accuracy of subclone identification within a large, complex cell population. In this study, we developed a subclone clustering method based on a fused lasso model, referred to as FLCNA, which can simultaneously detect CNAs in single-cell DNA sequencing (scDNA-seq) data. Spike-in simulations were conducted to evaluate the clustering and CNA detection performance of FLCNA, benchmarking it against existing copy number estimation methods (SCOPE, HMMcopy) in combination with commonly used clustering methods. Application of FLCNA to a scDNA-seq data set of breast cancer revealed different genomic variation patterns in neoadjuvant chemotherapy-treated samples and pretreated samples. We show that FLCNA is a practical and powerful method for subclone identification and CNA detection with scDNA-seq data.

EMT-related gene risk model establishment for prognosis and drug treatment efficiency prediction in hepatocellular carcinoma

This study was designed to evaluate the prognosis and pharmacological therapy sensitivity of epithelial mesenchymal transition-related genes (EMTRGs) that obtained from the EMTome database in hepatocellular carcinoma (HCC) using bioinformatical method. The expression status of EMTRGs were also investigated using the clinical information of HCC patients supported by TCGA database and the ICGC database to establish the TCGA cohort as the training set and the ICGC cohort as the validation set. Analyze the EMTRGs between HCC tissue and liver tissue in the TCGA cohort in the order of univariate COX regression, LASSO regression, and multivariate COX regression, and construct a risk model for EMTRGs. In addition, enrichment pathways, gene mutation status, immune infiltration, and response to drugs were also analyzed in the high-risk and low-risk groups of the TCGA cohort, and the protein expression status of EMTRGs was verified. The results showed a total of 286 differentially expressed EMTRGs in the TCGA cohort, and EZH2, S100A9, TNFRSF11B, SPINK5, and CCL21 were used for modeling. The TCGA cohort was found to have a worse outcome in the high-risk group of HCC patients, and the ICGC cohort confirmed this finding. In addition, EMTRGs risk score was shown to be an independent prognostic factor in both cohorts by univariate and multivariate COX regression. The results of GSEA analysis showed that most of the enriched pathways in the high-risk group were associated with tumor, and the pathways enriched in the low-risk group were mainly associated with metabolism. Patients in various risk groups had varying immunological conditions, and the high-risk group might benefit more from targeted treatments. To sum up, the EMTRGs risk model was developed to forecast the prognosis for HCC patients, and the model might be useful in assisting in the choice of treatment drugs for HCC patients.

Prostate Cancer Stem Cells: Biology and Treatment Implications

Stem cells differentiate into mature organ/tissue-specific cells at a steady pace under normal conditions, but their growth can be accelerated during the process of tissue healing or in the context of certain diseases. It is postulated that the proliferation and growth of carcinomas are sustained by the presence of a vital cellular compartment resembling stem cells residing in normal tissues: 'stem-like cancer cells' or cancer stem cells (CSCs). Mutations in prostate stem cells can lead to the formation of prostate cancer. Prostate CSCs (PCSCs) have been identified and partially characterized. These express surface markers include CD44, CD133, integrin α2β1, and pluripotency factors like OCT4, NANOG, and SOX2. Several signaling pathways are also over-activated, including Notch, PTEN/Akt/PI3K, RAS-RAF-MEK-ERK and HH. Moreover, PCSCs appear to induce resistance to radiotherapy and chemotherapy, while their presence has been linked to aggressive cancer behavior and higher relapse rates. The development of treatment policies to target PCSCs in tumors is appealing as radiotherapy and chemotherapy, through cancer cell killing, trigger tumor repopulation via activated stem cells. Thus, blocking this reactive stem cell mobilization may facilitate a positive outcome through cytotoxic treatment.

ScRNA-seq revealed an immunosuppression state and tumor microenvironment heterogeneity related to lymph node metastasis in prostate cancer

BACKGROUND

Metastasis is a crucial aspect of disease progression leading to death in patients with prostate cancer (PCa). However, its mechanism remains unclear. We aimed to explore the mechanism of lymph node metastasis (LNM) by analyzing the heterogeneity of tumor microenvironment (TME) in PCa using scRNA-seq.

METHODS

A total of 32,766 cells were obtained from four PCa tissue samples for scRNA-seq, annotated, and grouped. InferCNV, GSVA, DEG functional enrichment analysis, trajectory analysis, intercellular network evaluation, and transcription factor analysis were carried out for each cell subgroup. Furthermore, validation experiments targeting luminal cell subgroups and CXCR4 + fibroblast subgroup were performed.

RESULTS

The results showed that only EEF2 + and FOLH1 + luminal subgroups were present in LNM, and they appeared at the initial stage of luminal cell differentiation, which were comfirmed by verification experiments. The MYC pathway was enriched in the EEF2 + and FOLH1 + luminal subgroups, and MYC was associated with PCa LNM. Moreover, MYC did not only promote the progression of PCa, but also led to immunosuppression in TME by regulating PDL1 and CD47. The proportion of CD8 + T cells in TME and among NK cells and monocytes was lower in LNM than in the primary lesion, while the opposite was true for Th and Treg cells. Furthermore, these immune cells in TME underwent transcriptional reprogramming, including CD8 + T subgroups of CCR7 + and IL7R+, as well as M2-like monocyte subgroups expressing tumor-associated signature genes, like CCR7, SGKI, and RPL31. Furthermore, STEAP4+, ADGRF5 + and CXCR4+, and SRGNC + fibroblast subgroups were closely related to tumor progression, tumor metabolism, and immunosuppression, indicating their contributions in PCa metastasis. Meanwhile, The presence of CXCR4 + Fibroblasts in PCa was confirmed by polychromatic immunofluorescence.

CONCLUSIONS

The significant heterogeneity of luminal, immune, and interstitial cells in PCa LNM may not only directly contribute to tumor progression, but also indirectly result in TME immunosuppression, which may be the cause of metastasis in PCa and in which MYC played an role.

A statistical learning method for simultaneous copy number estimation and subclone clustering with single cell sequencing data

The availability of single cell sequencing (SCS) enables us to assess intra-tumor heterogeneity and identify cellular subclones without the confounding effect of mixed cells. Copy number aberrations (CNAs) have been commonly used to identify subclones in SCS data using various clustering methods, since cells comprising a subpopulation are found to share genetic profile. However, currently available methods may generate spurious results (e.g., falsely identified CNAs) in the procedure of CNA detection, hence diminishing the accuracy of subclone identification from a large complex cell population. In this study, we developed a CNA detection method based on a fused lasso model, referred to as FLCNA, which can simultaneously identify subclones in single cell DNA sequencing (scDNA-seq) data. Spike-in simulations were conducted to evaluate the clustering and CNA detection performance of FLCNA benchmarking to existing copy number estimation methods (SCOPE, HMMcopy) in combination with the existing and commonly used clustering methods. Interestingly, application of FLCNA to a real scDNA-seq dataset of breast cancer revealed remarkably different genomic variation patterns in neoadjuvant chemotherapy treated samples and pre-treated samples. We show that FLCNA is a practical and powerful method in subclone identification and CNA detection with scDNA-seq data.

CAPN8 involves with exhausted, inflamed, and desert immune microenvironment to influence the metastasis of thyroid cancer

BACKGROUND

Thyroid cancer (THCA) is the most prevalent malignant disease of the endocrine system, in which 5-year survival can attain about 95%, but patients with metastasis have a poor prognosis. Very little is known about the role of CAPN8 in the metastasis of THCA. In particular, the effect of CAPN8 on the tumor immune microenvironment (TIME) and immunotherapy response is unclear.

MATERIAL AND METHODS

Multiome datasets and multiple cohorts were acquired for analysis. Firstly, the expression and the prognostic value of CAPN8 were explored in public datasets and in vitro tumor tissues. Then, hierarchical clustering analysis was performed to identify the immune subtypes of THCA according to the expression of CAPN8 and the activities of related pathways. Subsequent analyses explored the different patterns of TIME, genetic alteration, DNA replication stress, drug sensitivity, and immunotherapy response among the three immune phenotypes. Finally, five individual cohorts of thyroid cancer were utilized to test the robustness and extrapolation of the three immune clusters.

RESULTS

CAPN8 was found to be a significant risk factor for THCA with a markedly elevated level of mRNA and protein in tumor tissues. This potential oncogene could induce the activation of epithelial-mesenchymal transition and E2F-targeted pathways. Three subtypes were identified for THCA, including immune exhausted, inflamed, and immune desert phenotypes. The exhausted type was characterized by a markedly increased expression of inhibitory receptors and infiltration of immune cells but was much more likely to respond to immunotherapy. The immune desert type was resistant to common chemotherapeutics with extensive genomic mutation and copy number variance.

CONCLUSION

The present study firstly explored the role of CAPN8 in the metastasis of THCA from the aspects of TIME. Three immune subtypes were identified with quite different patterns of prognosis, immunotherapy response, and drug sensitivity, providing novel insights for the treatment of THCA and helping understand the cross-talk between CAPN8 and tumor immune microenvironment.

HAUS5 Is A Potential Prognostic Biomarker With Functional Significance in Breast Cancer

Background

Breast cancer (BRCA) has become the most frequently appearing, lethal, and aggressive cancer with increasing morbidity and mortality. Previously, it was discovered that the HAUS5 protein is involved in centrosome integrity, spindle assembly, and the completion of the cytoplasmic division process during mitosis. By encouraging chromosome misdivision and aneuploidy, HAUS5 has the potential to cause cancer. The significance of HAUS5 in BRCA and the relationship between its expression and clinical outcomes or immune infiltration remains unclear.

Methods

Pan-cancer was analyzed by TIMER2 web and the expression differential of HAUS5 was discovered. The prognostic value of HAUS5 for BRCA was evaluated with KM plotter and confirmed with Gene Expression Omnibus (GEO) dataset. Following that, we looked at the relationship between the high and low expression groups of HAUS5 and breast cancer clinical indications. Signaling pathways linked to HAUS5 expression were discovered using Gene Set Enrichment Analysis (GSEA). The relative immune cell infiltrations of each sample were assessed using the CIBERSORT algorithm and ESTIMATE method. We evaluated the Tumor Mutation Burden (TMB) value between the two sets of samples with high and low HAUS5 expression, as well as the differences in gene mutations between the two groups. The proliferation changes of BRCA cells after knockdown of HAUS5 were evaluated by fluorescence cell counting and colony formation assay.

Result

HAUS5 is strongly expressed in most malignancies, and distinct associations exist between HAUS5 and prognosis in BRCA patients. Upregulated HAUS5 was associated with poor clinicopathological characteristics such as tumor T stage, ER, PR, and HER2 status. mitotic prometaphase, primary immunodeficiency, DNA replication, cell cycle related signaling pathways were all enriched in the presence of elevated HAUS5 expression, according to GSEA analysis. The BRCA microenvironment’s core gene, HAUS5, was shown to be related with invading immune cell subtypes and tumor cell stemness. TMB in the HAUS5-low expression group was significantly higher than that in the high expression group. The mutation frequency of 15 genes was substantially different in the high expression group compared to the low expression group. BRCA cells’ capacity to proliferate was decreased when HAUS5 was knocked down.

Conclusion

These findings show that HAUS5 is a positive regulator of BRCA progression that contributes to BRCA cells proliferation. As a result, HAUS5 might be a novel prognostic indicator and therapeutic target for BRCA patients.

Identification of key serum biomarkers for the diagnosis and metastatic prediction of osteosarcoma by analysis of immune cell infiltration

Background

The role of circular RNAs (circRNAs) and microRNAs (miRNAs) in osteosarcoma (OS) development has not been fully elucidated. Further, the contribution of the immune response to OS progression is not well defined. However, it is known that circRNAs and miRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of many cancers. Thus, the aim of this study was to identify novel key serum biomarkers for the diagnosis and metastatic prediction of OS by analysis of immune cell infiltration and associated RNA molecules.

Methods

Human OS differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified by analysis of microarray data downloaded from Gene Expression Omnibus (GEO) datasets. Further, characteristic patterns of OS-infiltrating immune cells were analyzed. On this basis, we identified statistically significant transcription factors. Moreover we performed pathway enrichment analysis, constructed protein–protein interaction networks, and devised competitive endogenous RNA (ceRNA) networks. Biological targets of the ceRNA networks were evaluated and potential OS biomarkers confirmed by RT-qPCR analysis of the patients’ serum.

Results

Seven differentially expressed circRNAs, 166 differentially expressed miRNAs, and 175 differentially expressed mRNAs were identified. An evaluation of cellular OS infiltration identified the highest level of infiltration by M0 macrophages, M2 macrophages, and CD8+ T cells, with M0 macrophages and CD8+ T cells as the most prominent. Significant patterns of tumor-infiltrating immune cells were identified by principal component analysis. Moreover, 185 statistically significant transcription factors were associated with OS. Further, in association with immune cell infiltration, hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A were identified as potential novel biomarkers for OS diagnosis. Of these, FAM98A had the most promise as a diagnostic marker for OS and OS metastasis. Most importantly, a novel diagnostic model consisting of these four biomarkers (hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A) was established with a 0.928 AUC value.

Conclusions

In summary, potential serum biomarkers for OS diagnosis and metastatic prediction were identified based on an analysis of immune cell infiltration. A novel diagnostic model consisting of these four promising serum biomarkers was established. Taken together, the results of this study provide a new perspective by which to understand immunotherapy of OS.

SOX9: Advances in Gynecological Malignancies

Transcription factors of the SOX family were first discovered in mammals in 1990. The sex-determining region Y box 9 belongs to the SOX transcription factor family. It plays an important role in inducing tissue and cell morphogenesis, survival, and many developmental processes. Furthermore, it has been shown to be an oncogene in many tumors. Gynecological malignancies are tumors that occur in the female reproductive system and seriously threaten the lives of patients. Common gynecological malignancies include ovarian cancer, cervical cancer, and endometrial cancer. So far, the molecular mechanisms related to the incidence and development of gynecological malignancies remain unclear. This makes it particularly important to discover their common causative molecule and thus provide an effective therapeutic target. In recent years, studies have found that multiple mechanisms are involved in regulating the expression of the sex-determining region Y box 9, leading to the occurrence and development of gynecological malignancies. In this review, we discuss the prognostic value of SOX9 expression and the potential of targeting SOX9 for gynecological malignancy treatment. We also discuss progress regarding the role of SOX9 in gynecological malignancy pathogenesis through its mediation of important mechanisms, including tumor initiation and proliferation, apoptosis, migration, invasion, chemoresistance, and stem cell maintenance.