A prognostic value of CD45RA+, CD45RO+, CCL20+ and CCR6+ expressing cells as 'immunoscore' to predict cervical cancer induced by HPV

mRNA-lncRNA gene expression signature in HPV-associated neoplasia and cervical cancer

Cervical cancer is one of the most frequent cancers in women and is associated with human papillomavirus (HPV) in 70 % of cases. Cervical cancer occurs because of progression of low-differentiated cervical intraepithelial neoplasia through grade 2 and 3 lesions. Along with the protein-coding genes, long noncoding RNAs (lncRNAs) play an important role in the development of malignant cell transformation. Although human papillomavirus is widespread, there is currently no well-characterized transcriptomic signature to predict whether this tumor will develop in the presence of HPV-associated neoplastic changes in the cervical epithelium. Changes in gene activity in tumors reflect the biological diversity of cellular phenotype and physiological functions and can be an important diagnostic marker. We performed comparative transcriptome analysis using open RNA sequencing data to assess differentially expressed genes between normal tissue, neoplastic epithelium, and cervical cancer. Raw data were preprocessed using the Galaxy platform. Batch effect correction, identification of differentially expressed genes, and gene set enrichment analysis (GSEA) were performed using R programming language packages. Subcellular localization of lncRNA was analyzed using Locate-R and iLoc-LncRNA 2.0 web services. 1,572 differentially expressed genes (DEGs) were recorded in the "cancer vs. control" comparison, and 1,260 DEGs were recorded in the "cancer vs. neoplasia" comparison. Only two genes were observed to be differentially expressed in the "neoplasia vs. control" comparison. The search for common genes among the most strongly differentially expressed genes among all comparison groups resulted in the identification of an expression signature consisting of the CCL20, CDKN2A, CTCFL, piR-55219, TRH, SLC27A6 and EPHA5 genes. The transcription level of the CCL20 and CDKN2A genes becomes increased at the stage of neoplastic epithelial changes and stays so in cervical cancer. Validation on an independent microarray dataset showed that the differential expression patterns of the CDKN2A and SLC27A6 genes were conserved in the respective gene expression comparisons between groups.

A Novel Notch-Related Gene Signature for Prognosis and Immune Response Prediction in Ovarian Cancer

Background and Objectives: Notch is a fascinating signaling pathway. It is extensively involved in tumor growth, cancer stem cells, metastasis, and treatment resistance and plays important roles in metabolic regulation, tumor microenvironment, and tumor immunity. However, the role of Notch in ovarian cancer (OC) has yet to be fully understood. Therefore, this study systematically described the expression, mutation, and copy number variation of genes in the Notch signaling pathway in OC and evaluated the relationship between gene mutation and Overall Survival (OS) prognosis. Materials and Methods: Notch risk score (NTRS) was established by univariate Cox regression analysis combined with Lasso regression analysis, and the efficacy of NTRS in predicting prognosis and immunotherapy response in patients with OC was verified. We further assessed the correlations of NTRS with clinical features, immune infiltration level, immune checkpoint expression, and immune characteristics. Additionally, differential expression and functions of the fourteen signature genes were confirmed via vitro assays. Results: The results showed that Notch genes (NTGs) were markedly differentiated between tumor and normal tissues, which may help to explain the high heterogeneity in the biological characteristics and therapeutic outcomes of human OC. A Notch risk (NTR) prognostic model based on 11 key NTGs was successfully constructed. Tumors with high Notch risk scores (NTRS) were independently associated with shorter overall survival and poorer immunotherapy outcomes. We further assessed the correlations of NTRS with immune characteristics. The results showed that NTGs play a key role in regulating the tumor immune microenvironment. Additionally, we validated the baseline and induced expressions of 14 prognosis-related NTGs in our own OC samples. In vitro assays confirmed that the knockdown of NCOR2 and APH1B and overexpression of HEY2 and SKP2 could inhibit the proliferation, invasion, and migration of OC cells. Conclusions: These findings emphasize that Notch multilayer changes are associated with the prognosis of patients with OC and the characteristics of immune cell infiltration. Our predictive signature may predict the prognosis and immunotherapy response of OC patients in an independent manner. NCOR2, APH1B, HEY2, and SKP2 may more prominently represent important indicators to improve patient prognosis.

A Comprehensive View of the Cancer-Immunity Cycle (CIC) in HPV-Mediated Cervical Cancer and Prospects for Emerging Therapeutic Opportunities

Cervical cancer (CC) is the fourth most common cancer in women worldwide, with more than 500,000 new cases each year and a mortality rate of around 55%. Over 80% of these deaths occur in developing countries. The most important risk factor for CC is persistent infection by a sexually transmitted virus, the human papillomavirus (HPV). Conventional treatments to eradicate this type of cancer are accompanied by high rates of resistance and a large number of side effects. Hence, it is crucial to devise novel effective therapeutic strategies. In recent years, an increasing number of studies have aimed to develop immunotherapeutic methods for treating cancer. However, these strategies have not proven to be effective enough to combat CC. This means there is a need to investigate immune molecular targets. An adaptive immune response against cancer has been described in seven key stages or steps defined as the cancer-immunity cycle (CIC). The CIC begins with the release of antigens by tumor cells and ends with their destruction by cytotoxic T-cells. In this paper, we discuss several molecular alterations found in each stage of the CIC of CC. In addition, we analyze the evidence discovered, the molecular mechanisms and their relationship with variables such as histological subtype and HPV infection, as well as their potential impact for adopting novel immunotherapeutic approaches.

Peripheral Blood T-lymphocyte Phenotypes in Mother-Child Pairs Stratified by the Maternal HPV Status: Persistent HPV16 vs. HPV-Negative: A Case-Control Study

Only few studies exist on the phenotype distribution of peripheral blood lymphocytes concerning persistent oral HPV infection. T-lymphocyte subsets were phenotyped in women who had persistent genital or oral HPV16 infection, using HPV-negative women as a reference group. A subset of 42 mothers and their children (n = 28), were stratified into two groups according to the mothers' HPV status. PBMCs from previously cryopreserved venous samples were immunophenotyped by flow cytometry. Proportions of the CD4⁺ or CD8⁺ lymphocytes by their immunophenotype subsets were compared between HPV-positive and -negative mothers and their children. The mean rank distribution of CD8⁺ memory cells was significantly higher among mothers with persistent genital HPV16 infection. The median levels of both the antigen-presenting CD4⁺ cells and activated CD8⁺ cells were significantly lower in mothers with persistent oral HPV16 infection. When oral and genital HPV16-persistors were analyzed as a group, a marker of terminal effector cells was significantly increased as compared to HPV-negative women. Significantly higher levels of activated CD4⁺, CD8⁺ and circulating CD8⁺ memory cells were found among children whose mothers had persistent oral HPV16 infection. Persistent HPV16 infections are associated with changes in peripheral blood T-lymphocyte subsets. The mother's persistent oral HPV16 infection possibly results in immune alterations in her offspring.

Immunoscore Combining CD8, FoxP3, and CD68-Positive Cells Density and Distribution Predicts the Prognosis of Head and Neck Cancer Patients

We assessed immune cell infiltrates to develop an immunoscore for prognosis and to investigate its correlation with the clinical data of patients with head and neck cancer. CD8, FoxP3, and CD68 markers were evaluated by immunohistochemistry in 258 carcinoma samples and positive cells were counted in stromal and intra-tumoral compartments. The RStudio software was used to assess optimal cut-offs to divide the population according to survival while the prognostic value was established by using Kaplan–Meier curves and Cox regression models for each immune marker alone and in combination. We found with univariate analysis that the infiltration of immune cells in both compartments was predictive for recurrence-free survival and overall survival. Multivariate analysis revealed that CD8+ density was an independent prognostic marker. Additionally, the combination of CD8, FoxP3, and CD68 in an immunoscore provided a significant association with overall survival (p = 0.002, HR = 9.87). Such an immunoscore stayed significant (p = 0.018, HR = 11.17) in a multivariate analysis in comparison to tumor stage and histological grade, which had lower prognostic values. Altogether, our analysis indicated that CD8, FoxP3, and CD68 immunoscore was a strong, independent, and significant prognostic marker that could be introduced into the landscape of current tools to improve the clinical management of head and neck cancer patients.

Prediction of Prognosis and Recurrence of Bladder Cancer by ECM-Related Genes

Background

Bladder cancer (BLCA) is one of the most common cancers and ranks ninth among all cancers. Extracellular matrix (ECM) genes activate a number of pathways that facilitate tumor development. This study is aimed at providing models to predict BLCA survival and recurrence by ECM genes.

Methods

Expression data from BLCA samples in GSE32894, GSE13507, GSE31684, GSE32548, and TCGA-BLCA cohorts were downloaded and analyzed. The ECM-related genes were obtained by differentially expressed gene analysis, stage-associated gene analysis, and random forest variable selection. The ECM was constructed in GSE32894 by the hub ECM-related genes and validated in GSE13507, GSE31684, GSE32548, and TCGA-BLCA cohorts. The correlations of the ECM score with cells (T cells, fibroblasts, etc.) and the response to immunotherapeutic drugs were investigated. Four machine learning models were selected and used to construct models to predict the recurrence of BLCA. A total of 15 paired BLCA and normal tissue specimens, human immortalized uroepithelial cell lines, and bladder cancer cell lines were selected for the validation of the difference in expression of FSTL1 between normal tissues and BLCA.

Results

Six ECM genes (CTHRC1, MMP11, COL10A1, FSTL1, SULF1, and COL5A3) were recognized to be the hub ECM-related genes. The ECM score of each BLCA patient was calculated using these six selected ECM-related genes. BLCA patients with a high ECM score group had significantly lower overall survival rates than patients in the low ECM score group. We found that the ECM score was positively associated with immune cells and fibroblasts and negatively correlated with tumor purity. When treated with immunotherapy, BLCA patients with a high ECM score presented a high response rate and better prognosis. We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence. Based on the RT-qPCR results of FSTL1 gene expression, there was an overall decrease in the mRNA expression of FSTL1 in cancer tissues compared to their adjacent normal tissues. Subsequent in vitro validation demonstrated that the FSTL1 expression was downregulated at the gene and protein level compared to that in SVH cells.

Conclusion

Taken together, our results indicate that ECM-related genes correlate with immune cells, overall survival, and recurrence of BLCA. This study provides a machine learning model for predicting the survival and recurrence of BLCA patients.

Immune Score Predicts Outcomes of Gastric Cancer Patients Treated with Adjuvant Chemoradiotherapy

Background

Substantial evidence has demonstrated that tumor-infiltrating lymphocytes (TILs) are correlated with patient prognosis. The TIL-based immune score (IS) affects prognosis in various cancers, but its prognostic impact in gastric cancer (GC) patients treated with adjuvant chemoradiotherapy remains unclear.

Methods

A total of 101 GC patients who received chemoradiotherapy after gastrectomy were retrospectively analyzed in this study. Immunohistochemistry staining for CD3+ and CD8+ T-cell counts in both tumor center (CT) and invasive margin (IM) regions was built into the IS. Patients were then divided into three groups based on their differential IS levels. The correlation between IS and clinical parameters was analyzed. The prognostic impact of IS and clinical parameters was evaluated using Kaplan-Meier analysis and Cox proportional hazard regression analysis. Receiver operating characteristic (ROC) curves were plotted to compare the area under the curve (AUC) of IS with other clinical parameters. Nomograms for disease-free survival (DFS) and overall survival (OS) prediction were constructed based on the identified parameters.

Results

Finally, 20 (19.8%), 57 (56.4%), and 24 (23.8%) GC patients were identified with low, intermediate, and high IS levels, respectively. GC patients with higher IS levels exhibited better DFS (p < 0.001) and OS (p < 0.001). IS was an independent prognostic factor for both DFS (p < 0.001) and OS (p < 0.001) in multivariate analysis. IS presented a better predictive ability than the traditional pathological tumor-node-metastasis (pTNM) staging system (AUC: 0.801 vs. 0.677 and 0.800 vs. 0.660, respectively) with respect to both DFS and OS. The C-index of the nomograms for DFS and OS prediction was 0.737 and 0.774, respectively.

Conclusions

IS is a strong predictive factor for both DFS and OS in GC patients treated with adjuvant chemoradiotherapy, which may complement the traditional pTNM staging system.

Recent progress of biomarkers in oral cancers

Oral cancers are the seventh most common cancer globally. While progresses in oral cancer treatment have been made, not all patients respond to these therapies in the same way. To overcome this difficulty, numerous studies have been devoted to identifying biomarkers, which enable early identification of patients who may benefit from a particular treatment modality or at risk for poor prognosis. Biomarkers are protein molecules, gene expression, DNA variants, or metabolites that are derived from tumors, adjacent normal tissue or bodily fluids, which can be acquired before treatment and during follow-up, thus extending their use to the evaluation of cancer progression and prediction of treatment outcome. In this review, we employed a basic significance level (<0.05) as the minimal requirement for candidate biomarkers. Effect sizes of the biomarkers in terms of odds ratio, hazard ratio, and area under the receiver operating characteristic curves were subsequently used to evaluate the potential of their clinical use. We identified the CCND1 from the tumor, human papillomavirus, HSP70, and IL-17 from the peripheral blood, and high density of CD45RO+ tumor-infiltrating lymphocytes as the clinically relevant biomarkers for oral cancers.