Integrated Analysis of Prognostic and Immune Associated Integrin Family in Ovarian Cancer

Preclinical efficacy of CBR-5884 against epithelial ovarian cancer cells by targeting the serine synthesis pathway

Reprogramming of the serine synthesis pathway (SSP) is intricately linked to the progression of epithelial ovarian cancer (EOC). CBR-5884, a selective small-molecule inhibitor targeting phosphoglycerate dehydrogenase (PHGDH), effectively impedes the de novo synthesis of serine within cancer cells. This study aimed to evaluate the inhibitory effect of CBR-5884 on EOC cells and delineate its specific mechanism, thereby proposing a novel therapeutic approach for treating EOC. The suppression of serine biosynthesis after CBR-5884 treatment was evaluated using RNA sequencing and a serine assay kit, and the results showed that CBR-5884 effectively downregulated serine biosynthesis in EOC cells, particularly those expressing high levels of PHGDH. In vitro studies revealed that CBR-5884 demonstrated significant antitumor effects and suppressed migration and invasion of EOC cells through down-regulation of the integrin subunit beta 4 (ITGB4)/extracellular signal-regulated kinase (ERK)/epithelial-mesenchymal transition signal axis. Additionally, CBR-5884 mitigated the stemness of EOC cells and heightened their sensitivity to chemotherapy. Moreover, in vivo studies revealed that CBR-5884 significantly delayed tumor growth, with histological analysis indicating the safety profile of CBR-5884. Finally, the patient-derived organoid (PDO) models were utilized to explore the preclinical efficacy of CBR-5884 against EOC cells, and the results unveiled that CBR-5884 impeded proliferation and downregulated the expression of ITGB4 in EOC PDO models. Our findings supports the anticancer properties of CBR-5884 in EOC cells exhibiting high PHGDH expression, manifesting through the suppression of proliferation, migration, and invasion, while enhancing chemotherapy sensitivity, suggesting that CBR-5884 holds promise as an efficacious strategy for the treatment of EOC.

Platinum-induced upregulation of ITGA6 promotes chemoresistance and spreading in ovarian cancer

Platinum (PT)-resistant Epithelial Ovarian Cancer (EOC) grows as a metastatic disease, disseminating in the abdomen and pelvis. Very few options are available for PT-resistant EOC patients, and little is known about how the acquisition of PT-resistance mediates the increased spreading capabilities of EOC. Here, using isogenic PT-resistant cells, genetic and pharmacological approaches, and patient-derived models, we report that Integrin α6 (ITGA6) is overexpressed by PT-resistant cells and is necessary to sustain EOC metastatic ability and adhesion-dependent PT-resistance. Using in vitro approaches, we showed that PT induces a positive loop that, by stimulating ITGA6 transcription and secretion, contributes to the formation of a pre-metastatic niche enabling EOC cells to disseminate. At molecular level, ITGA6 engagement regulates the production and availability of insulin-like growth factors (IGFs), over-stimulating the IGF1R pathway and upregulating Snail expression. In vitro data were recapitulated using in vivo models in which the targeting of ITGA6 prevents PT-resistant EOC dissemination and improves PT-activity, supporting ITGA6 as a promising druggable target for EOC patients.

ITGAL expression in non-small-cell lung cancer tissue and its association with immune infiltrates

Background

Integrin subunit alpha L (ITGAL) encodes an integrin component of LFA-1 and is a membrane receptor molecule widely expressed on leukocytes. It plays a key role in the interaction between white blood cells and other cells. There was a significant correlation between the expression of ITGAL and the tumor microenvironment in a number of cancers. However, experimental studies targeting ITGAL and immune cell infiltration in non-small-cell lung cancer (NSCLC) and the response to immune checkpoint inhibitor therapy are lacking.

Methods

Data were obtained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases to explore the relationship between ITGAL expression and prognosis, as well as the immune cell infiltration in patients with NSCLC. In addition, immunohistochemical staining for ITGAL and multiplex immunofluorescence (mIF) staining for ITGAL, CD20, CD68, CD4, and CD8 from tissue microarrays containing 118 tumor tissues and paired paracancerous tissues from patients with NSCLC were performed. The correlation between ITGAL expression and clinical factors, as well as the immunophenotypes of tumor-infiltrating immune cells, were also analyzed.

Results

In NSCLC tumor tissues, ITGAL was downregulated compared with matched paracancerous tissues, and low ITGAL expression was associated with a poor prognosis of NSCLC patients. Subsequently, immunohistochemistry results for tissue microarray showed that ITGAL expression was mainly elevated in tumor stroma and areas with highly infiltrated immune cells. ITGAL expression was higher in paracancerous tissues than tumor tissues. Furthermore, mIF results indicated that the patients with ITGAL-high expression tend had significantly higher CD8+ T cells, CD68+ macrophages, CD4+ T cells, and CD20+ B cells infiltration in their tumor tissues. Immunophenotypes were classified into three categories, that is deserted, excluded, and inflamed types, according to each kind of immune cell distribution in or around the cancer cell nest. MIF results showed that ITGAL expression level was correlated with the immunophenotypes. Furthermore, ITGAL expression was associated with the prognosis of NSCLC in patients with immune checkpoint inhibitor therapy and the patients with high ITGAL expression tends have better outcomes.

Conclusions

ITGAL may be used as a biomarker for assessing the immune microenvironment in patients with NSCLC.

Revealing the role of SPP1+ macrophages in glioma prognosis and therapeutic targeting by investigating tumor-associated macrophage landscape in grade 2 and 3 gliomas

BACKGROUND

Glioma is a highly heterogeneous brain tumor categorized into World Health Organization (WHO) grades 1-4 based on its malignancy. The suppressive immune microenvironment of glioma contributes significantly to unfavourable patient outcomes. However, the cellular composition and their complex interplays within the glioma environment remain poorly understood, and reliable prognostic markers remain elusive. Therefore, in-depth exploration of the tumor microenvironment (TME) and identification of predictive markers are crucial for improving the clinical management of glioma patients.

RESULTS

Our analysis of single-cell RNA-sequencing data from glioma samples unveiled the immunosuppressive role of tumor-associated macrophages (TAMs), mediated through intricate interactions with tumor cells and lymphocytes. We also discovered the heterogeneity within TAMs, among which a group of suppressive TAMs named TAM-SPP1 demonstrated a significant association with Epidermal Growth Factor Receptor (EGFR) amplification, impaired T cell response and unfavourable patient survival outcomes. Furthermore, by leveraging genomic and transcriptomic data from The Cancer Genome Atlas (TCGA) dataset, two distinct molecular subtypes with a different constitution of TAMs, EGFR status and clinical outcomes were identified. Exploiting the molecular differences between these two subtypes, we developed a four-gene-based prognostic model. This model displayed strong associations with an elevated level of suppressive TAMs and could be used to predict anti-tumor immune response and prognosis in glioma patients.

CONCLUSION

Our findings illuminated the molecular and cellular mechanisms that shape the immunosuppressive microenvironment in gliomas, providing novel insights into potential therapeutic targets. Furthermore, the developed prognostic model holds promise for predicting immunotherapy response and assisting in more precise risk stratification for glioma patients.

Heterogeneity of hepatocyte dynamics restores liver architecture after chemical, physical or viral damage

Midlobular hepatocytes are proposed to be the most plastic hepatic cell, providing a reservoir for hepatocyte proliferation during homeostasis and regeneration. However, other mechanisms beyond hyperplasia have been little explored and the contribution of other hepatocyte subpopulations to regeneration has been controversial. Thus, re-examining hepatocyte dynamics during regeneration is critical for cell therapy and treatment of liver diseases. Using a mouse model of hepatocyte- and non-hepatocyte- multicolor lineage tracing, we demonstrate that midlobular hepatocytes also undergo hypertrophy in response to chemical, physical, and viral insults. Our study shows that this subpopulation also combats liver impairment after infection with coronavirus. Furthermore, we demonstrate that pericentral hepatocytes also expand in number and size during the repair process and Galectin-9-CD44 pathway may be critical for driving these processes. Notably, we also identified that transdifferentiation and cell fusion during regeneration after severe injury contribute to recover hepatic function.

Identifying the prognosis implication, immunotherapy response prediction value, and potential targeted compound inhibitors of integrin subunit α3 (ITGA3) in human cancers

The integrin subunit α3 (ITGA3) is a member of the integrin alpha chain protein family, which could promote progression, metastasis, and invasion in some cancers. Still, its function in the tumor microenvironment (TME), cancer prognosis, and immunotherapy remains unclear. A multifaceted analysis of ITGA3 in pan-cancer utilizing various databases and online web tools revealed ITGA3 was aberrantly expressed in tumor tissues and upregulated in most cancers, which may be related to ITGA3 genomic alterations and methylation modification. In addition, ITGA3 was significantly correlated with the poor or better prognosis of cancer patients, immune-related pathways in hallmark, immune infiltration, and immune checkpoints, revealing a biological function of ITGA3 in the tumor progression, tumor microenvironment, and tumor immunity. We also found that ITGA3 could predict the response to tumor immunotherapy based on cytokine-treated samples and immunotherapy cohorts. ITGA3 may participate in shaping and regulating the tumor microenvironment to affect the tumor immune response, which was a promising immunotherapy response predictive biomarker and potential therapeutic target to work synergistically with cancer immunotherapy to boost the response and efficacy. Finally, potential targeted compound inhibitors and sensitive drugs were screened using databases ConnectivityMap (CMap) and CellMiner, and AutoDock Tools was used for molecular docking.

m5 C regulator-mediated methylation modification patterns and tumor microenvironment infiltration characteristics in acute myeloid leukemia

BACKGROUND

Recently, many studies have been conducted to examine immune response modification at epigenetic level, but the candidate effect of RNA 5-methylcytosine (m5 C) modification on tumor microenvironment (TME) of acute myeloid leukemia (AML) is still unknown at present.

METHODS

We assessed the patterns of m5 C modification among 417 AML cases by using nine m5 C regulators. Thereafter, we associated those identified modification patterns with TME cell infiltration features. Additionally, stepwise regression and LASSO Cox regression analyses were conducted for quantifying patterns of m5 C modification among AML cases to establish the m5 C-score. Meanwhile, we validated the expression of genes in the m5C-score model by qRT-PCR. Finally, the present work analyzed the association between m5 C-score and AML clinical characteristics and prognostic outcomes.

RESULTS

In total, three different patterns of m5 C modification (m5 C-clusters) were identified, and highly differentiated TME cell infiltration features were also identified. On this basis, evaluating patterns of m5 C modification in single cancer samples was important for evaluating the immune/stromal activities in TME and for predicting prognosis. In addition, the m5 C-score was established, which showed a close relation with the overall survival (OS) of test and training set samples. Moreover, multivariate Cox analysis suggested that our constructed m5 C-score served as the independent predicting factor for the prognosis of AML (hazard ratio = 1.57, 95% confidence interval = 1.38-1.79, p < 1e-5 ).

CONCLUSIONS

This study shows that m5 C modification may be one of the key roles in the formation of diversity and complexity of TME. Meanwhile, assessing the patterns of m5 C modification among individual cancer samples is of great importance, which provides insights into cell infiltration features within TME, thereby helping to develop relevant immunotherapy and predict patient prognostic outcomes.

Epithelial ovarian cancer is infiltrated by activated effector T cells co-expressing CD39, PD-1, TIM-3, CD137 and interacting with cancer cells and myeloid cells

Introduction

Despite predicted efficacy, immunotherapy in epithelial ovarian cancer (EOC) has limited clinical benefit and the prognosis of patients remains poor. There is thus a strong need for better identifying local immune dynamics and immune-suppressive pathways limiting T-cell mediated anti-tumor immunity.

Methods

In this observational study we analyzed by immunohistochemistry, gene expression profiling and flow cytometry the antigenic landscape and immune composition of 48 EOC specimens, with a focus on tumor-infiltrating lymphocytes (TILs).

Results

Activated T cells showing features of partial exhaustion with a CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ surface profile were exclusively present in EOC specimens but not in corresponding peripheral blood or ascitic fluid, indicating that the tumor microenvironment might sustain this peculiar phenotype. Interestingly, while neoplastic cells expressed several tumor-associated antigens possibly able to stimulate tumor-specific TILs, macrophages provided both co-stimulatory and inhibitory signals and were more abundant in TILs-enriched specimens harboring the CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ signature.

Conclusion

These data demonstrate that EOC is enriched in CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ T lymphocytes, a phenotype possibly modulated by antigen recognition on neoplastic cells and by a combination of inhibitory and co-stimulatory signals largely provided by infiltrating myeloid cells. Furthermore, we have identified immunosuppressive pathways potentially hampering local immunity which might be targeted by immunotherapeutic approaches.

A prognostic biomarker NRG1 promotes U-87 MG glioblastoma cell malignancy by inhibiting autophagy via ERBB2/AKT/mTOR pathway

Glioblastoma (GBM) is the most common and aggressive primary brain malignancy. Studies have shown that autophagy-related (ATG) genes play important roles in regulating GBM malignancy. However, the mechanism still needs to be fully elucidated. Based on clinical and gene expression information of GBM patients downloaded from The The Cancer Genome Atlas database, Kaplan-Meier, univariate Cox regression, least absolute shrinkage and selection operator regression and multivariate Cox regression were applied to construct a risk signature for GBM prognosis, followed by validation using receiver operating characteristic analysis. Next, Cell Counting Kit-8, wound healing assay, flow cytometry, monodansyl cadaverine autophagy staining assay, immunofluorescence staining and western blot, either in the absence or presence of ERBB2/AKT/mTOR inhibitors, were carried out in GBM U87 cell line to explore molecular pathway underlying GBM malignancy. A three-ATG-gene signature (HIF1A, ITGA3, and NGR1) was constructed for GBM prognosis with the greatest contribution from NRG1. In vitro experiments showed that NRG1 promoted U87 cell migration and proliferation by inhibiting autophagy, and ERBB2/AKT/mTOR is a downstream pathway that mediates the autophagy-inhibitory effects of NRG1. We constructed an ATG gene prognostic model for GBM and demonstrated that NRG1 inhibited autophagy by activating ERBB2/AKT/mTOR, promoting GBM malignancy, thus providing new insights into the molecular contribution of autophagy in GBM malignancy.

Regulation and Functions of α6-Integrin (CD49f) in Cancer Biology

Over the past decades, our knowledge of integrins has evolved from being understood as simple cell surface adhesion molecules to receptors that have a complex range of intracellular and extracellular functions, such as delivering chemical and mechanical signals to cells. Consequently, they actively control cellular proliferation, differentiation, and apoptosis. Dysregulation of integrin signaling is a major factor in the development and progression of many tumors. Many reviews have covered the broader integrin family in molecular and cellular studies and its roles in diseases. Nevertheless, further understanding of the mechanisms specific to an individual subunit of different heterodimers is more useful. Thus, we describe the current understanding of and exploratory investigations on the α6-integrin subunit (CD49f, VLA6; encoded by the gene itga6) in normal and cancer cells. The roles of ITGA6 in cell adhesion, stemness, metastasis, angiogenesis, and drug resistance, and as a diagnosis biomarker, are discussed. The role of ITGA6 differs based on several features, such as cell background, cancer type, and post-transcriptional alterations. In addition, exosomal ITGA6 also implies metastatic organotropism. The importance of ITGA6 in the progression of a number of cancers, including hematological malignancies, suggests its potential usage as a novel prognostic or diagnostic marker and useful therapeutic target for better clinical outcomes.

Tumor cell integrin β4 and tumor stroma E-/P-selectin cooperatively regulate tumor growth in vivo

BACKGROUND

The immunological composition of the tumor microenvironment has a decisive influence on the biological course of cancer and is therefore of profound clinical relevance. In this study, we analyzed the cooperative effects of integrin β4 (ITGB4) on tumor cells and E-/P-selectin on endothelial cells within the tumor stroma for regulating tumor growth by shaping the local and systemic immune environment.

METHODS

We used several preclinical mouse models for different solid human cancer types (xenograft and syngeneic) to explore the role of ITGB4 (shRNA-mediated knockdown in tumor cells) and E-/P-selectins (knockout in mice) for tumor growth; effects on apoptosis, proliferation and intratumoral signaling pathways were determined by histological and biochemical methods and 3D in vitro experiments; changes in the intratumoral and systemic immune cell composition were determined by flow cytometry and immunohistochemistry; chemokine levels and their attracting potential were measured by ELISA and 3D invasion assays.

RESULTS

We observed a very robust synergism between ITGB4 and E-/P-selectin for the regulation of tumor growth, accompanied by an increased recruitment of CD11b⁺ Gr-1^Hi cells with low granularity (i.e., myeloid-derived suppressor cells, MDSCs) specifically into ITGB4-depleted tumors. ITGB4-depleted tumors undergo apoptosis and actively attract MDSCs, well-known to promote tumor growth in several cancers, via increased secretion of different chemokines. MDSC trafficking into tumors crucially depends on E-/P-selectin expression. Analyses of clinical samples confirmed an inverse relationship between ITGB4 expression in tumors and number of tumor-infiltrating leukocytes.

CONCLUSIONS

These findings suggest a distinct vulnerability of ITGB4^Lo tumors for MDSC-directed immunotherapies.

Gene network landscape of mouse splenocytes reveals integrin complex as the A151 ODN-responsive hub molecule in the immune transcriptome

Homeostatic restoration of an inflammatory response requires quenching of the immune system after pathogen threats vanish. A continued assault orchestrated by host defense results in tissue destruction or autoimmunity. A151 is the epitome of synthetic oligodeoxynucleotides (ODNs) that curb the immune response by a subset of white corpuscles through repetitive telomere-derived TTAGGG sequences. Currently, the genuine effect of A151 on the immune cell transcriptome remains unknown. Here, we leveraged an integrative approach where weighted gene co-expression network analysis (WGCNA), differential gene expression analysis, and gene set enrichment analysis (GSEA) of our in-house microarray datasets aided our understanding of how A151 ODN suppresses the immune response in mouse splenocytes. Our bioinformatics results, together with experimental validations, indicated that A151 ODN acts on components of integrin complexes, Itgam and Itga6, to interfere with immune cell adhesion and thereby suppresses the immune response in mice. Moreover, independent lines of evidence in this work converged on the observation that cell adhesion by integrin complexes serves as a focal point for cellular response to A151 ODN treatment in immune cells. Taken together, the outcome of this study sheds light on the molecular basis of immune suppression by a clinically useful DNA-based therapeutic agent.

T cell-inflamed gene expression profile is associated with favorable disease-specific survival in non-hypermutated microsatellite-stable colorectal cancer patients

BACKGROUND

The anti-tumor immune response plays a key role in colorectal cancer (CRC) progression and survival. The T cell-inflamed gene expression profile (GEP) is a biomarker predicting response to checkpoint inhibitor immunotherapy across immunogenic cancer types, but the prognostic value in CRC is unknown. We evaluated associations with disease-specific survival, somatic mutations, and examined its differentially expressed genes and pathways among 84 sporadic CRC patients from the Seattle Colon Cancer Family Registry.

METHODS

Gene expression profiling was performed using Nanostring's nCounter PanCancer IO 360 panel. Somatic mutations were identified by a targeted DNA sequencing panel.

RESULTS

The T cell-inflamed GEP was positively associated with tumor mutation burden and microsatellite instability high (MSI-H). Higher T cell-inflamed GEP had favorable CRC-specific survival (hazard ratio [HR] per standard deviation unit = 0.50, p = 0.004) regardless of hypermutation or MSI status. Analysis of recurrently mutated genes having at least 10 mutation carriers, suggested that the T cell-inflamed GEP is positively associated with RYR1, and negatively associated with APC. However, these associations were attenuated after adjusting for hypermutation or MSI status. We also found that expression of genes RPL23, EPCAM, AREG and ITGA6, and the Wnt signaling pathway was negatively associated with the T cell-inflamed GEP, which might indicate immune-inhibitory mechanisms.

CONCLUSIONS

Our results show that the T cell-inflamed GEP is a prognostic biomarker in non-hypermutated microsatellite-stable CRC. This also suggests that patient stratification for immunotherapy within this CRC subgroup should be explored further. Moreover, reported immune-inhibitory gene expression signals may suggest targets for therapeutic combination with immunotherapy.

Comprehensive omics studies of p53 mutants in human cancer

The p53 is the master regulator of the cell known for regulating a large array of cellular processes. Inactivation of p53 by missense mutations is one of the leading causes of cancer. Some of these mutations endow p53 with selective oncogenic functions to promote tumor progression. Due to the vast array of mutations found in p53, the experimental studies showing the role of different mutant p53 as an oncogene are also expanding. In this review, we discuss the oncogenic roles of different p53 mutants at the cellular level identified by multi-omics tools. We discuss some of the therapeutic studies to tackle p53 mutants and their downstream targets identified by omics. We also highlight the future prospective and scope of further studies of downstream p53 targets by omics.

Prognostic implications of PPL expression in ovarian cancer

Periplakin (PPL) is a main member in plakin family, which plays important role in cellular adhesion complexes supporting and cytoskeletal integrity supplying. PPL was reported to be a potential biomarker candidate for several types of cancers. However, the biological functions and underlying mechanisms of PPL in ovarian cancer (OV) remain unclear. In the present study, we used GEPIA 2, Human Protein Atlas, Oncomine, LinkedOmics, Kaplan-Meier Plotter, STRING, CytoHubba plug-in and TIMER to determine the associations among PPL expression, prognosis, and immune cell infiltration in OV. RT-qPCR and IHC analysis were conducted to validated the role of PPL in an independent OV cohort. Compared with the normal ovary tissues, the levels of PPL mRNA and protein expression were both obviously higher in OV tumors from multiple datasets (P < 0.05), and a poor survival was observed to be strongly correlated with high PPL expression (P < 0.05). Moreover, the results were further validated by RT-qPCR and IHC analysis in an independent OV cohort. A gene-clinical nomogram was constructed, including PPL mRNA expression and clinical factors in TCGA. Functional network analysis suggested that PPL participates in the important pathways like Wnt signaling pathway, MAPK signaling pathway. Ten hub genes (LAMC2, PXN, LAMA3, LAMB3, LAMA5, ITGA3, TLN1, ACTN4, ACTN1, and ITGB4) were identified to be positively associated with PPL. Furthermore, PPL expression was negatively correlated with infiltrating levels of CD4+ T cell, macrophages, neutrophils, and dendritic cells. In conclusion, PPL may be an unfavorable prognostic biomarker candidate in OV, which was also correlated with immune infiltrating and function in immunotherapy response.

Bioinformatic Investigation of Micro RNA-802 Target Genes, Protein Networks, and Its Potential Prognostic Value in Breast Cancer

Background

An increasing number of studies have suggested that unveiling the molecular network of miRNAs may provide novel therapeutic targets or biomarkers. In this study, we investigated the probable molecular functions that are related to microRNA-802 (miR-802) and evaluated its prognostic value in breast cancer utilizing bioinformatics tools.

Methods

PPI network, pathway enrichment and transcription factor analysis were applied to obtain hub genes among overlapping genes of four miRNA target prediction databases. Prognosis value assessments and expression analysis of hub genes using bioinformatics tools, as well as their literature validation were performed.

Results

Our results showed a significant correlation of the miR-802 overexpression with poor patient survival rate (BC, p=2.7e-5). We determined 247 target genes significant for GO and KEGG terms. Analysis of TFs by TRUST showed that RUNX3, FOXO3, and E2F1 are possible TFs that regulate the miR-802 expression and target genes network. According to our analysis; 21 genes might have an important function in miR-802 molecular processes and regulatory networks. The result shows that among these 21 genes, 8 genes (CASC3, ITGA4, AGO3, TARDBP, MED13L, SF1, SNRPE and CRNKL1) are positively correlated with patient survival. Therefore these genes could be considered and experimentally evaluated as a prognostic biomarker for breast cancer.

Conclusion

The comprehensive bioinformatics study on miR-802 target genes provided insight into miR-802 mediated pathways and processes. Furthermore, representing candidate target genes by prognostic values indicates the potential clinical application of miR-802 in breast cancer.

Identification of the Immune Signatures for Ovarian Cancer Based on the Tumor Immune Microenvironment Genes

Ovarian cancer (OV) is a deadly gynecological cancer. The tumor immune microenvironment (TIME) plays a pivotal role in OV development. However, the TIME of OV is not fully known. Therefore, we aimed to provide a comprehensive network of the TIME in OV. Gene expression data and clinical information from OV patients were obtained from the Cancer Genome Atlas Program (TCGA) database. Non-negative Matrix Factorization, NMFConsensus, and nearest template prediction algorithms were used to perform molecular clustering. The biological functions of differentially expressed genes (DEGs) were identified using Metascape, gene set enrichment analysis (GSEA), gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The copy number variations (CNVs), single nucleotide polymorphisms (SNPs) and tumor mutation burden were analyzed using Gistic 2.0, R package maftools, and TCGA mutations, respectively. Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data and CIBERSORT were utilized to elucidate the TIME. Moreover, external data from the International Cancer Genome Consortium (ICGC) and ArrayExpress databases were used to validate the signature. All 361 samples from the TCGA OV dataset were classified into Immune Class and non-Immune Class with immune signatures. By comparing the two classes, we identified 740 DEGs that accumulated in immune-related, cancer-related, inflammation-related biological functions and pathways. There were significant differences in the CNVs between the Immune and non-Immune Classes. The Immune Class was further divided into immune-activated and immune-suppressed subtypes. There was no significant difference in the top 20 genes in somatic SNPs among the three groups. In addition, the immune-activated subtype had significantly increased proportions of CD4 memory resting T cells, T cells, M1 macrophages, and M2 macrophages than the other two groups. The qRT-PCR results indicated that the mRNA expression levels of RYR2, FAT3, MDN1 and RYR1 were significantly down-regulated in OV compared with normal tissues. Moreover, the signatures of the TIME were validated using ICGC cohort and the ArrayExpress cohort. Our study clustered the OV patients into an immune-activated subtype, immune-suppressed subtype, and non-Immune Class and provided potential clues for further research on the molecular mechanisms and immunotherapy strategies of OV.

Evaluation of ITGA3 as a Biomarker of Progression and Recurrence in Papillary Thyroid Carcinoma

Objective

To investigate the expression of ITGA3 and its association with clinical outcomes in papillary thyroid carcinoma (PTC).

Methods

The expression level, association with clinicopathologic characteristics, co-expressed genes, signaling pathways of ITGA3 in thyroid cancer were comprehensively analyzed using bioinformatics analysis through multiple public gene databases. PTC specimens and cell lines were used to verify the results of bioinformatics analysis.

Results

Data mining based on the Oncomine database revealed that ITGA3 expression in classical PTC and tall cell variant PTC was much higher than that in normal thyroid tissue except the follicular variant PTC. Analysis based on The Cancer Genome Atlas (TCGA) database showed that the expression of ITGA3 varies greatly in pathological stages, pathological types, tumor invasion stages, and lymph node metastasis stages of thyroid carcinoma. High expression level of ITGA3 was correlated with tumor regional invasion and lymph node metastasis. Multivariate analysis using logistic regression model showed that high expression of ITGA3 was a risk factor that associated with PTC recurrence and lymph node metastasis. Survival analysis showed that patients with high expression of ITGA3 in PTC had a poorer relapse-free survival (RFS) than patients with low expression of ITGA3 (P < 0.05). Immunohistochemistry experiments showed that the expression of ITGA3 in recurrent thyroid cancer tissues was stronger than that in no-recurrent thyroid cancer tissues (P < 0.05). Knockdown of ITGA3 by sh-RNA in PTC cell lines suppresses cell viability and invasive and migrating capacity.

Conclusion

ITGA3 is overexpressed in PTC, especially in those with higher tumor invasion grades and lymph node metastasis, and was associated with recurrence and poor RFS of PTC. High expression of ITGA3 may have the potential role of predicting PTC recurrence and lymph node metastasis.

Genome-wide association and functional interrogation identified a variant at 3p26.1 modulating ovarian cancer survival among Chinese women

Ovarian cancer survival varies considerably among patients, to which germline variation may also contribute in addition to mutational signatures. To identify genetic markers modulating ovarian cancer outcome, we performed a genome-wide association study in 2130 Chinese ovarian cancer patients and found a hitherto unrecognized locus at 3p26.1 to be associated with the overall survival (P_combined = 8.90 × 10⁻¹⁰). Subsequent statistical fine-mapping, functional annotation, and eQTL mapping prioritized a likely casual SNP rs9311399 in the non-coding regulatory region. Mechanistically, rs9311399 altered its enhancer activity through an allele-specific transcription factor binding and a long-range interaction with the promoter of a lncRNA BHLHE40-AS1. Deletion of the rs9311399-associated enhancer resulted in expression changes in several oncogenic signaling pathway genes and a decrease in tumor growth. Thus, we have identified a novel genetic locus that is associated with ovarian cancer survival possibly through a long-range gene regulation of oncogenic pathways.

N-Glycoproteomics Study of Putative N-Glycoprotein Biomarkers of Drug Resistance in MCF-7/ADR Cells

Currently, drug resistance of anti-cancer therapy has become the main cause of low survival rate and poor prognosis. Full understanding of drug resistance mechanisms is an urgent request for further development of anti-cancer therapy and improvement of prognosis. Here we present our N-glycoproteomics study of putative N-glycoprotein biomarkers of drug resistance in doxorubicin resistance breast cancer cell line michigan cancer foundation-7 (MCF-7/ADR) relative to parental michigan cancer foundation-7 (MCF-7) cells. Intact N-glycopeptides (IDs) from MCF-7/ADR and MCF-7 cells were enriched with zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC), labeled with stable isotopic diethylation (SIDE), and analyzed with C18-RPLC-MS/MS (HCD with stepped normalized collision energies); these IDs were identified with database search engine GPSeeker, and the differentially expressed intact N-glycopeptides (DEGPs) were quantified with GPSeekerQuan. With target-decoy searches and control of spectrum-level FDR ≤ 1%, 322 intact N-glycopeptides were identified; these intact N-glycopeptides come from the combination of 249 unique peptide backbones (corresponding to 234 intact N-glycoproteins) and 90 monosaccharide compositions (corresponding to 248 putative N-glycosites). The sequence structures of 165 IDs were confirmed with structure-diagnostic fragment ions. With the criteria of observation at least twice among the three technical replicates, ≥ 1.5-fold change and p value < 0.05, 20 DEGPs were quantified, where five of them were up-regulated and 15 of them were down-regulated; the corresponding intact N-glycoproteins as putative markers of drug resistance were discussed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-021-00029-8.

Single-cell analysis revealed that IL4I1 promoted ovarian cancer progression

Background

Ovarian cancer was one of the leading causes of female deaths. Patients with OC were essentially incurable and portends a poor prognosis, presumably because of profound genetic heterogeneity limiting reproducible prognostic classifications.

Methods

We comprehensively analyzed an ovarian cancer single-cell RNA sequencing dataset, GSE118828, and identified nine major cell types. Relationship between the clusters was explored with CellPhoneDB. A malignant epithelial cluster was confirmed using pseudotime analysis, CNV and GSVA. Furthermore, we constructed the prediction model (i.e., RiskScore) consisted of 10 prognosis-specific genes from 2397 malignant epithelial genes using the LASSO Cox regression algorithm based on public datasets. Then, the prognostic value of Riskscore was assessed with Kaplan–Meier survival analysis and time-dependent ROC curves. At last, a series of in-vitro assays were conducted to explore the roles of IL4I1, an important gene in Riskscore, in OC progression.

Results

We found that macrophages possessed the most interaction pairs with other clusters, and M2-like TAMs were the dominant type of macrophages. C0 was identified as the malignant epithelial cluster. Patients with a lower RiskScore had a greater OS (log-rank P < 0.01). In training set, the AUC of RiskScore was 0.666, 0.743 and 0.809 in 1-year, 3-year and 5-year survival, respectively. This was also validated in another two cohorts. Moreover, downregulation of IL4I1 inhibited OC cells proliferation, migration and invasion.

Conclusions

Our work provide novel insights into our understanding of the heterogeneity among OCs, and would help elucidate the biology of OC and provide clinical guidance in prognosis for OC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03123-7.

Single-Cell RNA-Sequencing Portraying Functional Diversity and Clinical Implications of IFI6 in Ovarian Cancer

Ovarian cancer (OC) is one of the most lethal gynecologic malignancies. Most patients die of metastasis due to a lack of other treatments aimed at improving the prognosis of OC patients. In the present study, we use multiple methods to identify prognostic S1 as the dominant subtype in OC, possessing the most ligand-receptor pairs with other cell types. Based on markers of S1, the consensus clustering algorithm is used to explore the clinical treatment subtype in OC. As a result, we identify two clusters associated with distinct survival and drug response. Notably, IFI6 contributes to the cluster classification and seems to be a vital gene in OC carcinogenesis. Functional enrichment analysis demonstrates that its functions involve G2M and cisplatin resistance, and downregulation of IFI6 suppresses proliferation capabilities and significantly potentiates cisplatin-induced apoptosis of OC cells in vitro. To explore possible mechanisms of IFI6 influencing OC proliferation and cisplatin resistance, GSEA is conducted and shows that IFI6 is positively correlated with the NF-κB pathway, which is validated by RT-qPCR. Significantly, we develop a prognostic model including IFI6, RiskScore, which is an independent prognostic factor and presents encouraging prognostic values. Our findings provide novel insights into elucidating the biology of OC based on single-cell RNA-sequencing. Moreover, this approach is potentially helpful for personalized anti-cancer strategies and predicting outcomes in the setting of OC.

Comprehensive Analysis of the Expression and Prognosis for Laminin Genes in Ovarian Cancer

Survival is low in ovarian cancer (OC). Most OC patients demonstrate advanced metastases, and recurrence is common. Dysregulation of laminin interactions is associated with cancer development. However, it is unknown whether laminin subunits can be considered as biomarkers for OC diagnosis, prognosis, and treatment. We used cBioPortal, GEO, ONCOMINE, GEPIA, Human Protein Atlas, Kaplan-Meier Plotter, TIMER, and Metascape to determine the associations among laminin expression, prognosis, and immune cell infiltration in OC. LAMA5, LAMB3, and LAMC2 mRNAs and LAMA3, LAMB1/B2/B3, and LAMC1/C2 proteins were overexpressed in OC tissues compared with normal ovaries. LAMA4, LAMB1, and LAMC1 mRNA upregulation was positively correlated with worse overall survival (OS) and progression-free survival (PFS) in OC. Elevated LAMA2 and LAMC2 mRNA expression levels were related to better PFS or OS, respectively. The results speculated that LAMA5 could potentially be a good prognostic factor in OC. Its expression proves valuable for predicting OS in patients diagnosed with stage Ⅳ and grade 3 OC and PFS in patients diagnosed with all OC stages or grades. LAMB3 and LAMC2 expression was correlated with platinum resistance development. ROC analysis of laminins in OC sets revealed that LAMA2/A4/A5, LAMB1/B2/B3, and LAMC2 could be used to differentiate between malignant tumors and non-neoplastic tissues. LAMA1/A5 and LAMC1 were significantly and negatively correlated with various tumor immune infiltrates (TILs), especially with dendritic cells, CD8⁺ T cells or neutrophil. LAMA4 and LAMB1 might be associated with tumor purity in OC. Overall, LAMA5 and LAMC1 could help predict OC survival and diagnosis and might be deemed important OC oncogenes.

Integrin α2β1 Represents a Prognostic and Predictive Biomarker in Primary Ovarian Cancer

Currently, the same first-line chemotherapy is administered to almost all patients suffering from primary ovarian cancer. The high recurrence rate emphasizes the need for precise drug treatment in primary ovarian cancer. Being crucial in ovarian cancer progression and chemotherapeutic resistance, integrins became promising therapeutic targets. To evaluate its prognostic and predictive value, in the present study, the expression of integrin α2β1 was analyzed immunohistochemically and correlated with the survival data and other therapy-relevant biomarkers. The significant correlation of a high α2β1-expression with the estrogen receptor alpha (ERα; p = 0.035) and epithelial growth factor receptor (EGFR; p = 0.027) was observed. In addition, high α2β1-expression was significantly associated with a low number of tumor-infiltrating immune cells (CD3 intratumoral, p = 0.017; CD3 stromal, p = 0.035; PD-1 intratumoral, p = 0.002; PD-1 stromal, p = 0.049) and the lack of PD-L1 expression (p = 0.005). In Kaplan–Meier survival analysis, patients with a high expression of integrin α2β1 revealed a significant shorter progression-free survival (PFS, p = 0.035) and platinum-free interval (PFI, p = 0.034). In the multivariate Cox regression analysis, integrin α2β1 was confirmed as an independent prognostic factor for both PFS (p = 0.021) and PFI (p = 0.020). Dual expression of integrin α2β1 and the hepatocyte growth factor receptor (HGFR; PFS/PFI, p = 0.004) and CD44v6 (PFS, p = 0.000; PFI, p = 0.001; overall survival [OS], p = 0.025) impaired survival. Integrin α2β1 was established as a prognostic and predictive marker in primary ovarian cancer with the potential to stratify patients for chemotherapy and immunotherapy, and to design new targeted treatment strategies.