Whole-transcriptome analysis of flow-sorted cervical cancer samples reveals that B cell expressed TCL1A is correlated with improved survival

The immune microenvironment of cancer of the uterine cervix

While several treatment choices exist for cervical cancer, such as surgical therapy, chemotherapy, and radiotherapy, some patients will still show poor prognosis. HPV infection is a principal factor for cervical cancer development, from early inflammation to proliferation, angiogenesis, and neoplastic growth. While HPV T-cell responses exist, the tumor seems to evade the immune system upon its tolerance. The latter suggests the existence of a confluent tumor microenvironment responsible for the evasion tactics employed by the neoplasm. Therefore, novel biomarkers governing prognosis and treatment planning must be developed, with several studies tackling the significance of the tumor microenvironment in the genesis, development, proliferation, and overall response of cervical cancer during neoplastic processes. This review aims to analyze and contemplate the characteristics of the tumor microenvironment and its role in prognosis, progression, evasion, and invasion, including therapeutic outcome and overall survival.

TCL1A+ B cells predict prognosis in triple-negative breast cancer through integrative analysis of single-cell and bulk transcriptomic data

Triple-negative breast cancer (TNBC) is an aggressive subtype with limited treatment options and high mortality rates. It remains a prevailing clinical need to distinguish whether the patient can benefit from therapy, such as chemotherapy. By integrating single-cell and global transcriptome data, we have for the first time identified TCL1A+ B cell functions that are prognostically relevant in TNBC. This finding broadens the perspective of traditional tumor-infiltrating lymphocytes in predicting survival, especially the potential value of B cells in TNBC. Single-cell RNA-seq data from five TNBC patients were collected to identify the association between immune cell populations and clinical outcomes. Functional analysis was according to gene set enrichment analysis using pathways from MsigDB. Subsequently, the gene signature of TCL1A+ B cells based on differential expression genes of TCL1A+ B cells versus other immune cells was used to explore the correlation with tumor microenvironment (TME) and construct a prognostic signature using a non-parametric and unsupervised method. We identified TCL1A+ B cells as a cluster of B cells associated with clinical outcomes in TNBC. Functional analysis demonstrated its function in B cell activation and regulation of immune response. The highly enriched TCL1A+ B cell population was found to be associated with a thermal TME with anti-tumor effects. A high abundance of TCL1A+ B cell population is positively correlated with a favorable therapeutic outcome, as indicated by longer overall survival. The present study suggests that TCL1A+ B cells play a key role in the treatment and prognostic prediction of TNBC, although further studies are needed to validate our findings. Moreover, the integration of transcriptome data at various resolutions provides a viable approach for the discovery of novel prognostic markers.

Coordinated single-cell tumor microenvironment dynamics reinforce pancreatic cancer subtype

Bulk analyses of pancreatic ductal adenocarcinoma (PDAC) samples are complicated by the tumor microenvironment (TME), i.e. signals from fibroblasts, endocrine, exocrine, and immune cells. Despite this, we and others have established tumor and stroma subtypes with prognostic significance. However, understanding of underlying signals driving distinct immune and stromal landscapes is still incomplete. Here we integrate 92 single cell RNA-seq samples from seven independent studies to build a reproducible PDAC atlas with a focus on tumor-TME interdependence. Patients with activated stroma are synonymous with higher myofibroblastic and immunogenic fibroblasts, and furthermore show increased M2-like macrophages and regulatory T-cells. Contrastingly, patients with 'normal' stroma show M1-like recruitment, elevated effector and exhausted T-cells. To aid interoperability of future studies, we provide a pretrained cell type classifier and an atlas of subtype-based signaling factors that we also validate in mouse data. Ultimately, this work leverages the heterogeneity among single-cell studies to create a comprehensive view of the orchestra of signaling interactions governing PDAC.

Prognostic significance and immune infiltration of microenvironment-related signatures in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is 1 of the highly fatal and most aggressive types of malignancies and accounts for the vast majority of Pancreatic Cancer. Numerous studies have reported that the tumor microenvironment (TME) was significantly correlated with the oncogenesis, progress, and prognosis of various malignancies. Therefore, mining of TME-related genes is reasonably important to improve the overall survival of patients with PDAC.The Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm was applied to identify differential expressed genes. Functional and pathway enrichment analyses, protein-protein interaction network construction and module analysis, overall survival analysis and tumor immune estimation resource database analysis were then performed on differential expressed genes.Data analysis indicated that higher immune scores were correlated with better overall survival (P = 0.033). Differential expression analysis obtained 90 intersection genes influencing both stromal and immune scores. Among these intersection genes, CA9, EBI3, SPOCK2, WDFY4, CD1D, and CCL22 were significantly correlated with overall survival in PDAC patients. Moreover, multivariate Cox analysis revealed that CA9, SPOCK2, and CD1D were the most significant prognostic genes, and were closely correlated with immune infiltration in TCGA cohort. Further analysis indicated that CD1D were significantly related with immune cell biomarkers for PDAC patients.In summary, our findings provide a more comprehensive insight into TME and show a list of prognostic immune associated genes in PDAC. However, further studies on these genes need to be performed to gain additional understanding of the association between TME and prognosis in PDAC.

Identification of a 5-Gene-Based Scoring System by WGCNA and LASSO to Predict Prognosis for Rectal Cancer Patients

Background

Although accumulating evidence suggested that a molecular signature panel may be more effective for the prognosis prediction than routine clinical characteristics, current studies mainly focused on colorectal or colon cancers. No reports specifically focused on the signature panel for rectal cancers (RC). Our present study was aimed at developing a novel prognostic signature panel for RC.

Methods

Sequencing (or microarray) data and clinicopathological details of patients with RC were retrieved from The Cancer Genome Atlas (TCGA-READ) or the Gene Expression Omnibus (GSE123390, GSE56699) database. A weighted gene coexpression network was used to identify RC-related modules. The least absolute shrinkage and selection operator analysis was performed to screen the prognostic signature panel. The prognostic performance of the risk score was evaluated by survival curve analyses. Functions of prognostic genes were predicted based on the interaction proteins and the correlation with tumor-infiltrating immune cells. The Human Protein Atlas (HPA) tool was utilized to validate the protein expression levels.

Results

A total of 247 differentially expressed genes (DEGs) were commonly identified using TCGA and GSE123390 datasets. Brown and yellow modules (including 77 DEGs) were identified to be preserved for RC. Five DEGs (ASB2, GPR15, PRPH, RNASE7, and TCL1A) in these two modules constituted the optimal prognosis signature panel. Kaplan-Meier curve analysis showed that patients in the high-risk group had a poorer prognosis than those in the low-risk group. Receiver operating characteristic (ROC) curve analysis demonstrated that this risk score had high predictive accuracy for unfavorable prognosis, with the area under the ROC curve of 0.915 and 0.827 for TCGA and GSE56699 datasets, respectively. This five-mRNA classifier was an independent prognostic factor. Its predictive accuracy was also higher than all clinical factor models. A prognostic nomogram was developed by integrating the risk score and clinical factors, which showed the highest prognostic power. ASB2, PRPH, and GPR15/TCL1A were predicted to function by interacting with CASQ2/PDK4/EPHA67, PTN, and CXCL12, respectively. TCL1A and GPR15 influenced the infiltration levels of B cells and dendritic cells, while the expression of PRPH was positively associated with the abundance of macrophages. HPA analysis supported the downregulation of PRPH, RNASE7, CASQ2, EPHA6, and PDK4 in RC compared with normal controls.

Conclusion

Our immune-related signature panel may be a promising prognostic indicator for RC.

Multiregion single-cell sequencing reveals the transcriptional landscape of the immune microenvironment of colorectal cancer

The tumor microenvironment is a complex ecosystem formed by distinct and interacting cell populations, and its composition is related to cancer prognosis and response to clinical treatment. In this study, we have taken the advantage of two single-cell RNA sequencing technologies (Smart-seq2 and DNBelab C4) to generate an atlas of 15,115 immune and nonimmune cells from primary tumors and hepatic metastases of 18 colorectal cancer (CRC) patients. We observed extensive changes in the proportions and functional states of T cells and B cells in tumor tissues, compared to those of paired non-tumor tissues. Importantly, we found that B cells from early CRC tumor were identified to be pre-B like expressing tumor suppressors, whereas B cells from advanced CRC tumors tended to be developed into plasma cells. We also identified the association of IgA+ IGLC2+ plasma cells with poor CRC prognosis, and demonstrated a significant interaction between B-cell and myeloid-cell signaling, and found CCL8+ cycling B cells/CCR5+ T-cell interactions as a potential antitumoral mechanism in advanced CRC tumors. Our results provide deeper insights into the immune infiltration within CRC, and a new perspective for the future research in immunotherapies for CRC.

Markers of Angiogenesis, Lymphangiogenesis, and Epithelial-Mesenchymal Transition (Plasticity) in CIN and Early Invasive Carcinoma of the Cervix: Exploring Putative Molecular Mechanisms Involved in Early Tumor Invasion

The establishment of a proangiogenic phenotype and epithelial-to-mesenchymal transition (EMT) are considered as critical events that promote the induction of invasive growth in epithelial tumors, and stimulation of lymphangiogenesis is believed to confer the capacity for early dissemination to cancer cells. Recent research has revealed substantial interdependence between these processes at the molecular level as they rely on common signaling networks. Of great interest are the molecular mechanisms of (lymph-)angiogenesis and EMT associated with the earliest stages of transition from intraepithelial development to invasive growth, as they could provide the source of potentially valuable tools for targeting tumor metastasis. However, in the case of early-stage cervical cancer, the players of (lymph-)angiogenesis and EMT processes still remain substantially uncharacterized. In this study, we used RNA sequencing to compare transcriptomes of HPV(+) preinvasive neoplastic lesions and early-stage invasive carcinoma of the cervix and to identify (lymph-)angiogenesis- and EMT-related genes and pathways that may underlie early acquisition of invasive phenotype and metastatic properties by cervical cancer cells. Second, we applied flow cytometric analysis to evaluate the expression of three key lymphangiogenesis/EMT markers (VEGFR3, MET, and SLUG) in epithelial cells derived from enzymatically treated tissue specimens. Overall, among 201 differentially expressed genes, a considerable number of (lymph-)angiogenesis and EMT regulatory factors were identified, including genes encoding cytokines, growth factor receptors, transcription factors, and adhesion molecules. Pathway analysis confirmed enrichment for angiogenesis, epithelial differentiation, and cell guidance pathways at transition from intraepithelial neoplasia to invasive carcinoma and suggested immune-regulatory/inflammatory pathways to be implicated in initiation of invasive growth of cervical cancer. Flow cytometry showed cell phenotype-specific expression pattern for VEGFR3, MET, and SLUG and revealed correlation with the amount of tumor-infiltrating lymphocytes at the early stages of cervical cancer progression. Taken together, these results extend our understanding of driving forces of angiogenesis and metastasis in HPV-associated cervical cancer and may be useful for developing new treatments.

Prognostic genes in the tumor microenvironment in cervical squamous cell carcinoma

Cervical squamous cell carcinoma (CSCC) is one of the most commonly occurring gynecological malignancies. Because CSCC is a biologically heterogeneous disease, its prognosis varies. Therefore, identifying prognostic biomarkers that reflect its biological heterogeneity could lead to better interventions for patients with a poor prognosis. This study used the ESTIMATE algorithm to identify immune related prognostic genes within the tumor microenvironment of CSCC. The results revealed that high immune scores were associated with better overall survival (P = 0.029). Differential expression analysis revealed 384 intersection genes influencing both the immune and stromal scores. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed the 384 intersection genes to be mainly enriched for T cell activation, the region of the membrane, carbohydrate binding, and cytokine-cytokine receptor interaction. Among them, 149 immune genes were predictive of overall survival in CSCC. These findings provide a more comprehensive understanding of immune genes within the tumor microenvironment as well as a list of immune genes prognostic in CSCC.

Biomarker Identification for Cancer Disease Using Biclustering Approach: An Empirical Study

This paper presents an exhaustive empirical study to identify biomarkers using two approaches: frequency-based and network-based, over seventeen different biclustering algorithms and six different cancer expression datasets. To systematically analyze the biclustering algorithms, we perform enrichment analysis, subtype identification and biomarker identification. Biclustering algorithms such as C&C, SAMBA and Plaid are useful to detect biomarkers by both approaches for all datasets except prostate cancer. We detect a total of 102 gene biomarkers using frequency-based method out of which 19 are for blood cancer, 36 for lung cancer, 25 for colon cancer, 13 for multi-tissue cancer and 9 for prostate cancer. Using the network-based approach we detect a total of 41 gene biomarkers of which 15 are from blood cancer, 12 from lung cancer, 6 from colon cancer, 7 from multi-tissue cancer and 1 from prostate cancer dataset. We further extend our network analysis over some biclusters and detect some gene biomarkers not detected earlier by both frequency-based or network-based approach. We expand our work on breast cancer miRNA expression data to evaluate the performance of the biclustering algorithms. We detect 19 breast cancer biomarkers by frequency-based method and 5 by network-based method for the miRNA dataset.

Interactome analysis of gene expression profiles of cervical cancer reveals dysregulated mitotic gene clusters

Cervical cancer is the second most common malignancy in women worldwide. HPV infections are the leading cause of cervical cancer. Although progress has been made in understanding cervical cancer, knowledge of oncogenic gene clusters that participate in squamous-cell mitosis is still lacking. We performed a computational analysis with qRT-PCR validation of gene expression profiles of cervical cancer tissues. Genes involved in muscle contraction and development were downregulated in cervical cancer tissues, suggesting decreased muscle function in cervical cancer. Among the genes that were upregulated in cervical cancer tissues, several groups of genes were found to interact with each other and synergistically participate in multiple stages of mitosis including DNA replication, cell cycle progression, and cell division. An analysis of gene regulatory networks showed that replicative helicase proteins (MCM2, MCM4, MCM5, MCM6, and MCM10) and DNA polymerases (PLOA1/E2/E3/Q) have enhanced DNA replication in cervical cancer. A group of kinases, cyclins, and transcriptional factors were found to promote cell cycle transitions from G1 phase to S phase and from G2 phase to M phase. Those proteins included CDK1, CCNA2, CCNB2, and TFDP2. Moreover, a set of motor proteins (KIF11, KIF14 and KIF4A) and their partner PRC1 were found to mediate cytokinesis during cervical cancer progression. Those findings present a better understanding of the mechanism of mitosis in cervical cancer from an interactomic perspective and provide potential targets for anticancer therapies.

Spatial intratumoral heterogeneity and temporal clonal evolution in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is among the most common malignancies, but little is known about its spatial intratumor heterogeneity (ITH) and temporal clonal evolutionary processes. To address this, we performed multiregion whole-exome sequencing on 51 tumor regions from 13 ESCCs, and multiregion global methylation profiling on three of these 13 cases. We found an average of 35.8% heterogeneous somatic mutations with strong evidence of ITH. Half of driver mutations located on the branches targeted oncogenes, including PIK3CA, NFE2L2, MTOR, etc. By contrast, the majority of truncal and clonal driver mutations occurred in tumor suppressor genes, including TP53, KMT2D, ZNF750, etc. Interestingly, the phyloepigenetic trees robustly recapitulated the topologic structures of the phylogenetic ones, indicating the possible relationship between genetic and epigenetic alterations. Our integrated investigations of the spatial ITH and clonal evolution provide an important molecular foundation for enhanced understanding of the tumorigenesis and progression of ESCC.

Overexpression of the oncostatin-M receptor in cervical squamous cell carcinoma is associated with epithelial-mesenchymal transition and poor overall survival

Background:

Copy-number gain of the oncostatin-M receptor (OSMR) occurs frequently in cervical squamous cell carcinoma (SCC) and is associated with adverse clinical outcome. We previously showed that OSMR overexpression renders cervical SCC cells more sensitive to the major ligand oncostatin-M (OSM), which increases migration and invasion in vitro. We hypothesised that a major contribution to this phenotype would come from epithelial–mesenchymal transition (EMT).

Methods:

We performed a comprehensive integrated study, involving in vitro cell line studies, in vivo animal models and numerous clinical samples from a variety of anatomical sites.

Results:

In independent sets of cervical, head/neck and lung SCC tissues, OSMR expression levels correlated with multiple EMT-associated phenotypic markers and transcription factors. OSM treatment of OSMR overexpressing cervical SCC cells produced consistent EMT changes and increased tumour sphere formation in suspension culture. In a mouse model, OSMR overexpressing SCC cells treated with OSM showed significant increases in lung colonisation. The biological effects of exogenous OSM were mirrored by highly significant adverse overall survival in cervical SCCs with OSMR overexpression (N=251).

Conclusions:

OSM:OSMR interactions are able to induce EMT, increased cancer stem cell-like properties and enhanced lung colonisation in SCC cells. These changes are likely to contribute to the highly significant adverse outcome associated with OSMR overexpression in cervical SCCs.

The double-edge role of B cells in mediating antitumor T-cell immunity: Pharmacological strategies for cancer immunotherapy

Emerging evidence reveals the controversial role of B cells in antitumor immunity, but the underlying mechanisms have to be explored. Three latest articles published in the issue 521 of Nature in 2015 reconfirmed the puzzling topic and put forward some explanations of how B cells regulate antitumor T-cell responses both positively and negatively. This paper attempts to demonstrate that different B-cell subpopulations have distinct immunological properties and that they are involved in either antitumor responses or immunosuppression. Recent studies supporting the positive and negative roles of B cells in tumor development were summarized comprehensively. Several specific B-cell subpopulations, such as IgG(+), IgA(+), IL-10(+), and regulatory B cells, were described in detail. The mechanisms underlying the controversial B-cell effects were mainly attributed to different B-cell subpopulations, different B-cell-derived cytokines, direct B cell-T cell interaction, different cancer categories, and different malignant stages, and the immunological interaction between B cells and T cells is mediated by dendritic cells. Promising B-cell-based antitumor strategies were proposed and novel B-cell regulators were summarized to present interesting therapeutic targets. Future investigations are needed to make sure that B-cell-based pharmacological strategies benefit cancer immunotherapy substantially.