A distinct subset of urothelial cells with enhanced EMT features promotes chemotherapy resistance and cancer recurrence by increasing COL4A1-ITGB1 mediated angiogenesis.

Drug resistance and tumor recurrence remain clinical challenges in the treatment of urothelial carcinoma (UC). However, the underlying mechanism is not fully understood. Here, we performed single-cell RNA sequencing and identified a subset of urothelial cells with epithelial-mesenchymal transition (EMT) features (EMT-UC), which is significantly correlated with chemotherapy resistance and cancer recurrence. To validate the clinical significance of EMT-UC, we constructed EMT-UC like cells by introducing overexpression of two markers, Zinc Finger E-Box Binding Homeobox 1 (ZEB1) and Desmin (DES), and examined their histological distribution characteristics and malignant phenotypes. EMT-UC like cells were mainly enriched in UC tissues from patients with adverse prognosis and exhibited significantly elevated EMT, migration and gemcitabine tolerance in vitro. However, EMT-UC was not specifically identified from tumorous tissues, certain proportion of them were also identified in adjacent normal tissues. Tumorous EMT-UC highly expressed genes involved in malignant behaviors and exhibited adverse prognosis. Additionally, tumorous EMT-UC was associated with remodeled tumor microenvironment (TME), which exhibited high angiogenic and immunosuppressive potentials compared with the normal counterparts. Furthermore, a specific interaction of COL4A1 and ITGB1 was identified to be highly enriched in tumorous EMT-UC, and in the endothelial component. Targeting the interaction of COL4A1 and ITGB1 with specific antibodies significantly suppressed tumorous angiogenesis and alleviated gemcitabine resistance of UC. Overall, our findings demonstrated that the driven force of chemotherapy resistance and recurrence of UC was EMT-UC mediated COL4A1-ITGB1 interaction, providing a potential target for future UC treatment.

Dynamic changes in macrophage subtypes during lung cancer progression and metastasis at single-cell resolution.

Background: Lung cancer remains a major global health challenge. Macrophages (Macs) are one important component of tumor microenvironments (TMEs); however, their prognostic relevance to lung cancer is currently unknown due to the complexity of their phenotypes. Methods: In the present study, reanalysis and atlas reconstruction of downloaded single-cell RNA sequencing (scRNAseq) data were used to systematically compare the component and transcriptional changes in Mac subtypes across different stages of lung cancer. Results: We found that with the progression of lung cancer, the proportion of alveolar macrophages (aMacs) gradually decreased, while the proportions of Macs and monocytes (Monos) gradually increased, suggesting a chemotaxis process followed by a Mono-Mac differentiation process. Meanwhile, through ligand-receptor (LR) screening, we identified 9 Mac-specific interactions that were enriched during the progression and metastasis of lung cancer, which could potential promote M2 polarization or the infiltration of M2 Macs. Moreover, we found that the expression of SPP1 in Macs increased with lung cancer progression, and identified 9 genes that were correlated with the expression of SPP1 in Macs, which might also contribute to the immunosuppression process in lung cancer. Conclusions: Our results revealed detailed changes in Macs at different stages of lung cancer progression and metastasis and provided potential therapeutic targets that could be used in future lung cancer treatments.

Monoacylglycerol lipase regulates macrophage polarization and cancer progression in uveal melanoma and pan-cancer.

Background: Although lipid metabolism has been proven to play a key role in the development of cancer, its significance in uveal melanoma (UM) has not yet been elucidated in the available literature. Methods: To identify the expression patterns of lipid metabolism in 80 UM patients from the TCGA database, 47 genes involved in lipid metabolism were analyzed. Consensus clustering revealed two distinct molecular groups. ESTIMATE, TIMER, and ssGSEA analyses were done to identify the differences between the two subgroups in tumor microenvironment (TME) and immune state. Using Cox regression and Lasso regression analysis, a risk model based on differentially expressed genes (DEGs) was developed. To validate the expression of monoacylglycerol lipase (MGLL) and immune infiltration in diverse malignancies, a pan-cancer cohort from the UCSC database was utilized. Next, a single-cell sequencing analysis on UM patients from the GEO data was used to characterize the lipid metabolism in TME and the role of MGLL in UM. Finally, in vitro investigations were utilized to study the involvement of MGLL in UM. Results: Two molecular subgroups of UM patients have considerably varied survival rates. The majority of DEGs between the two subgroups were associated with immune-related pathways. Low immune scores, high tumor purity, a low number of immune infiltrating cells, and a comparatively low immunological state were associated with a more favorable prognosis. An examination of GO and KEGG data demonstrated that the risk model based on genes involved with lipid metabolism can accurately predict survival in patients with UM. It has been demonstrated that MGLL, a crucial gene in this paradigm, promotes the proliferation, invasion, and migration of UM cells. In addition, we discovered that MGLL is strongly expressed in macrophages, specifically M2 macrophages, which may play a function in the M2 polarization of macrophages and M2 macrophage activation in cancer cells. Conclusion: This study demonstrates that the risk model based on lipid metabolism may be useful for predicting the prognosis of patients with UM. By promoting macrophage M2 polarization, MGLL contributes to the evolution of malignancy in UM, suggesting that it may be a therapeutic target for UM.

Transcription factor E2F8 is a therapeutic target in the basal-like subtype of breast cancer.

Introduction: Tumorigenesis in breast cancers usually accompanied by the dysregulation of transcription factors (TFs). Abnormal amplification of TFs leads aberrant expression of its downstream target genes. However, breast cancers are heterogeneous disease with different subtypes that have distinguished clinical behaviours, and the identification of prognostic TFs may enable to provide diagnosis and treatment of breast cancer based on subtypes, especially in Basal-like breast cancer. Methods: The RNA-sequencing was performed to screen differential TFs in breast cancer subtypes. The GEPIA dataset analysis was used to analyze the genes expression in invasive breast carcinoma. The expression of MYBL2, HOXC13, and E2F8 was verified by qRT-PCR assay in breast cancers. The depiction analysis of co-expressed proteins was revealed using the STRING datasets. The cellular infiltration level analysis by the TISIDB and TIMER databases. The transwell assay was performed to analyze cellular migration and invasion. CCK-8 assay was used to evaluate cellular drug susceptibility for docetaxel treatment. Predicted targeted drugs in breast cancers by GSCA Lite database online. Results: Kaplan-Meier plotter suggested that high expression of both E2F8 and MYBL2 in Basal-like subtype had a poor relapse-free survival. Functional enrichment results identified that apoptosis, cell cycle, and hormone ER pathway were represented the crucial regulation pathways by both E2F8 and MYBL2. In the meantime, database analysis indicated that high expression of E2F8 responded to chemotherapy, while those patients of high expression of MYBL2 responded to endocrinotherapy, and a positive correlation between the expression of E2F8 and PD-L1/CTLA4. Our cell line experiments confirmed the importance of E2F8 and MYBL2 in proliferation and chemotherapy sensitivity, possibly, the relationship with PD-L1. Additionally, we also observed that the up-regulation of E2F8 was accompanied with higher enrichments of CD4+ T cells and CD8+ T cells in breast cancers. Conclusion: Taken together, our findings elucidated a prospective target in Basal-like breast cancer, providing underlying molecular biomarkers for the development of breast cancer treatment.

Identification of novel prognostic biomarkers for osteosarcoma: a bioinformatics analysis of differentially expressed genes in the mesenchymal stem cells from single-cell sequencing data set.

Background: Mesenchymal stem cells (MSCs) play a crucial role in osteosarcoma (OS) growth and progression. This study conducted a bioinformatics analysis of a single-cell ribonucleic acid sequencing data set and explored the MSC-specific differentially expressed genes (DEGs) in advanced OS. Methods: MSC-specific DEGs from GSE152048 was extracted using Seurat R package. These DEGs were then subjected to the functional analysis, and several key genes were further identified and underwent a prognosis analysis. Results: A total of 234 upregulated and 280 downregulated DEGs were identified between the MSCs and other cells, and a total of 188 upregulated and 158 downregulated DEGs were identified between the MSCs and osteoblastic cells. The Gene Ontology (GO) functional analysis showed that the specific DEGs between the MSCs and osteoblastic cells were enriched in GO terms such as "collagen catabolic process", "positive regulation of pathway-restricted SMAD protein phosphorylation", "osteoblast differentiation", "regulation of release of cytochrome c from mitochondria" and "interleukin-1 production". The specific DEGs between the MSCs and osteoblastic cells were subjected to a protein-protein interaction network analysis. Further, a survival analysis of 20 genes with combined scores >0.94 revealed that the low expression of ANXA1 (annexin A1) and TPM1 (tropomyosin 1) was associated with the shorter overall survival of OS patients, while the high expression of FDPS (farnesyl pyrophosphate synthase), IFITM5 (interferon-induced transmembrane protein 5), FKBP11 (FKBP prolyl isomerase 11), SP7, and SQLE (squalene epoxidase) was associated with the shorter overall survival of OS patients. In a further analysis, we compared the expression of ANXA1, FDPS, IFITM5, FKBP11, SP7, SQLE, and TPM1 between the MSCs and high-grade OS cells. Further validation studies using the GSE42352 data set revealed that ANXA1, FKBP11, SP7, and TPM1 were more upregulated in the MSCs than the high-grade OS cells, while FDPS, IFITM5, and SQLE were more downregulated in the MSCs than the high-grade OS cells. Conclusions: Our bioinformatics analysis revealed 7 hub genes derived from the specific DEGs between the MSCs and osteoblastic cells. The 7 hub genes may serve as potential prognostic biomarkers for patients with OS.

Yin Yang 1 promotes aggressive cell growth in high-grade breast cancer by directly transactivating kinectin 1.

Invasive cancer growth and metastasis account for the poor prognosis of high-grade breast cancer. Recently, we reported that kinectin 1 (KTN1), a member of the kinesin-binding protein family, promotes cell invasion of triple-negative breast cancer and high-grade breast cancer cells by augmenting the NF-κB signaling pathway. However, the upstream mechanism regulating KTN1 is unknown. Therefore, this functional study was performed to decipher the regulatory cohort of KTN1 in high-grade breast cancer. Bioinformatic analysis indicated that transcription factor Yin Yang 1 (YY1) was a potential transactivator of KTN1. High YY1 expression correlated positively with pathological progression and poor prognosis of high-grade breast cancer. Additionally, YY1 promoted cell invasive growth both in vitro and in vivo, in a KTN1-dependent manner. Mechanistically, YY1 could transactivate the KTN1 gene promoter. Alternatively, YY1 could directly interact with a co-factor, DEAD-box helicase 3 X-linked (DDX3X), which significantly co-activated YY1-mediated transcriptional expression of KTN1. Moreover, DDX3X augmented YY1-KTN1 signaling-promoted invasive cell growth of breast cancer. Importantly, overexpression of YY1 enhanced tumor aggressive growth in a mouse breast cancer model. Our findings established a novel DDX3X-assisted YY1-KTN1 regulatory axis in breast cancer progression, which could lead to the development novel therapeutic targets for breast cancer.

Kinectin 1 promotes the growth of triple-negative breast cancer via directly co-activating NF-kappaB/p65 and enhancing its transcriptional activity.

Triple-negative breast cancer (TNBC) is the most challenging subtype of breast cancer. Various endeavor has been made to explore the molecular biology basis of TNBC. Herein, we reported a novel function of factor Kinectin 1 (KTN1) as a carcinogenic promoter in TNBC. KTN1 expression in TNBC was increased compared with adjacent tissues or luminal or Her2 subtypes of breast cancer, and TNBC patients with high KTN1 expression have poor prognosis. In functional studies, knockdown of KTN1 inhibited the proliferation and invasiveness of TNBC both in vitro and in vivo, while overexpression of KTN1 promoted cancer cell proliferation and invasiveness. RNA-seq analysis revealed that the interaction of cytokine-cytokine receptor, particularly CXCL8 gene, was upregulated by KTN1, which was supported by the further experiments. CXCL8 depletion inhibited the tumorigenesis and progression of TNBC. Additionally, rescue experiments validated that KTN1-mediated cell growth acceleration in TNBC was dependent on CXCL8 both in vitro and in vivo. Furthermore, it was found that KTN1 enhanced the phosphorylation of NF-κB/p65 protein at Ser536 site, and specifically bound to NF-κB/p65 protein in the nucleus and cytoplasm of cells. Moreover, the transcription of CXCL8 gene was directly upregulated by the complex of KTN1 and NF-κB/p65 protein. Taken together, our results elucidated a novel mechanism of KTN1 gene in TNBC tumorigenesis and progression. KTN1 may be a potential molecular target for the development of TNBC treatment.

Identification of a distinct luminal subgroup diagnosing and stratifying early stage prostate cancer by tissue-based single-cell RNA sequencing.

BACKGROUND: The highly intra-tumoral heterogeneity and complex cell origination of prostate cancer greatly limits the utility of traditional bulk RNA sequencing in finding better biomarker for disease diagnosis and stratification. Tissue specimens based single-cell RNA sequencing holds great promise for identification of novel biomarkers. However, this technique has yet been used in the study of prostate cancer heterogeneity. METHODS: Cell types and the corresponding marker genes were identified by single-cell RNA sequencing. Malignant states of different clusters were evaluated by copy number variation analysis and differentially expressed genes of pseudo-bulks sequencing. Diagnosis and stratification of prostate cancer was estimated by receiver operating characteristic curves of marker genes. Expression characteristics of marker genes were verified by immunostaining. RESULTS: Fifteen cell groups including three luminal clusters with different expression profiles were identified in prostate cancer tissues. The luminal cluster with the highest copy number variation level and marker genes enriched in prostate cancer-related metabolic processes was considered the malignant cluster. This cluster contained a distinct subgroup with high expression level of prostate cancer biomarkers and a strong distinguishing ability of normal and cancerous prostates across different pathology grading. In addition, we identified another marker gene, Hepsin (HPN), with a 0.930 area under the curve score distinguishing normal tissue from prostate cancer lesion. This finding was further validated by immunostaining of HPN in prostate cancer tissue array. CONCLUSION: Our findings provide a valuable resource for interpreting tumor heterogeneity in prostate cancer, and a novel candidate marker for prostate cancer management.

Mutational Pattern in Multiple Pulmonary Nodules Are Associated With Early Stage Lung Adenocarcinoma.

The clinical significance of mutation in multiple pulmonary nodules is largely limited by single gene mutation-directed analysis and lack of validation of gene expression profiles. New analytic strategy is urgently needed for comprehensive understanding of genomic data in multiple pulmonary nodules. In this study, we performed whole exome sequencing in 16 multiple lung nodules and 5 adjacent normal tissues from 4 patients with multiple pulmonary nodules and decoded the mutation information from a perspective of cellular functions and signaling pathways. Mutated genes as well as mutation patterns shared in more than two lesions were identified and characterized. We found that the number of mutations or mutated genes and the extent of protein structural changes caused by different mutations is positively correlated with the degree of malignancy. Moreover, the mutated genes in the nodules are associated with the molecular functions or signaling pathways related to cell proliferation and survival. We showed a developing pattern of quantity (the number of mutations/mutated genes) and quality (the extent of protein structural changes) in multiple pulmonary nodules. The mutation and mutated genes in multiple pulmonary nodules are associated with cell proliferation and survival related signaling pathways. This study provides a new perspective for comprehension of genomic mutational data and might shed new light on deciphering molecular evolution of early stage lung adenocarcinoma.

Draft genome of Brugia pahangi: high similarity between B. pahangi and B. malayi.

BACKGROUND: Efforts to completely eradicate lymphatic filariasis from human population may be challenged by the emergence of Brugia pahangi as another zoonotic lymphatic filarial nematode. In this report, a genomic study was conducted to understand this species at molecular level. METHODS: After blood meal on a B. pahangi-harbouring cat, the Aedes togoi mosquitoes were maintained to harvest infective third stage larvae, which were then injected into male Mongolian gerbils. Subsequently, adult B. pahangi were obtained from the infected gerbil for genomic DNA extraction. Sequencing and subsequently, construction of genomic libraries were performed. This was followed by genomic analyses and gene annotation analysis. By using archived protein sequences of B. malayi and a few other nematodes, clustering of gene orthologs and phylogenetics were conducted. RESULTS: A total of 9687 coding genes were predicted. The genome of B. pahangi shared high similarity to that B. malayi genome, particularly genes annotated to fundamental processes. Nevertheless, 166 genes were considered to be unique to B. pahangi, which may be responsible for the distinct properties of B. pahangi as compared to other filarial nematodes. In addition, 803 genes were deduced to be derived from Wolbachia, an endosymbiont bacterium, with 44 of these genes intercalate into the nematode genome. CONCLUSIONS: The reporting of B. pahangi draft genome contributes to genomic archive. Albeit with high similarity to B. malayi genome, the B. pahangi-unique genes found in this study may serve as new focus to study differences in virulence, vector selection and host adaptability among different Brugia spp.

Genome of the Chinese tree shrew.

Chinese tree shrews (Tupaia belangeri chinensis) possess many features valuable in animals used as experimental models in biomedical research. Currently, there are numerous attempts to employ tree shrews as models for a variety of human disorders: depression, myopia, hepatitis B and C virus infections, and hepatocellular carcinoma, to name a few. Here we present a publicly available annotated genome sequence for the Chinese tree shrew. Phylogenomic analysis of the tree shrew and other mammalians highly support its close affinity to primates. By characterizing key factors and signalling pathways in nervous and immune systems, we demonstrate that tree shrews possess both shared common and unique features, and provide a genetic basis for the use of this animal as a potential model for biomedical research.