A novel seven‑miRNA prognostic model to predict overall survival in head and neck squamous cell carcinoma patients

MiR-548k suppresses apoptosis in breast cancer cells by affecting PTEN/PI3K/AKT signaling pathway

Breast cancer is the most aggressive and fatal form of cancer among women globally. Although the role of some miRNAs that are often dysregulated in breast cancer has been deciphered, the regulatory function of others still remains unknown. The current study was aimed at determining the biological role and underlying mechanism of miR-548k in breast cancer. In this study, the significant overexpression of miR-548k in breast cancer tissues compared to adjacent normal tissues was confirmed. Also, bioinformatics analysis indicated that PTEN, as a negative regulator of PI3K/AKT signaling pathway, was a potential target of miR-548k, and its expression was downregulated in breast cancer tissues rather than normal tissues. Furthermore, the ectopic increase of miR-548k decreased the expression of PTEN in breast cancer, suggesting that PTEN is one of the potential downstream targets of miR-548k. Besides, functional analysis was conducted to assess the capability of miR-548k to alter apoptosis along with the changed expression levels of miR-548k in breast cancer cells. Based on this investigation, forced increase of miR-548k disrupted programmed cell death in MCF-7 cells. Apart from this, in silico study of miR-548 family supported its association with the main components of PI3K/Akt signaling pathway, opening a prospective research area in cancer therapy. In brief, suppression of PTEN partly mediated by miR-548k diminished apoptosis and promoted cell proliferation through PI3K/Akt pathway in breast cancer, suggesting a novel therapeutic axis, miR-548k/PTEN/ PI3K/Akt, for treatment of breast cancer in the future.

The Role of Perioperative C-Reactive Protein in Predicting the Prognosis of Epithelial Ovarian Carcinoma

Background

Increasing epidemiological evidence supported that chronic inflammatory factors might be involved in the carcinogenesis and progression of various cancers. The present study tried to investigate the prognostic value of perioperative C-reactive protein (CRP) in prognosis of patients with epithelial ovarian carcinoma (EOC) from a tertiary university teaching hospital.

Methods

The cutoff value of CRP was calculated according to receiver operating characteristic (ROC) curve. Variables were compared using Chi-square test. Progress-free survival (PFS) and overall survival (OS) time were assessed by Kaplan-Meier (KM) survival analysis and Log rank test based on serum CRP level. Univariate and multivariate Cox regression analyses were applied for assessing the relationship between clinicopathological parameters and survival.

Results

Higher perioperative CRP levels (preoperative ≥5.15 mg/L and postoperative ≥72.45 mg/L) were significantly associated with serous tumor, high-grade, advanced stage, elevated preoperative CA125, suboptimal surgery, chemotherapy resistance, recurrence and death in EOC (P < 0.01). KM analysis suggested patients with elevated preoperative, postoperative and perioperative CRP had shorter survival (P < 0.01). Elevated perioperative CRP was an independent risk factor for PFS (HR 1.510, 95% CI 1.124-2.028; P = 0.006) and OS (HR 1.580, 95% CI 1.109-2.251; P = 0.011). Similar results were obtained for elevated preoperative CRP. Subgroup analysis further suggested that elevated perioperative CRP was also an independent risk factor for prognosis in advanced stage and serous EOC.

Conclusion

Elevated perioperative CRP was an independent risk factor for poorer prognosis of EOC, particularly in advanced stage and serous patients.

A Novel Bayesian Framework Infers Driver Activation States and Reveals Pathway-Oriented Molecular Subtypes in Head and Neck Cancer

Head and neck squamous cell cancer (HNSCC) is an aggressive cancer resulting from heterogeneous causes. To reveal the underlying drivers and signaling mechanisms of different HNSCC tumors, we developed a novel Bayesian framework to identify drivers of individual tumors and infer the states of driver proteins in cellular signaling system in HNSCC tumors. First, we systematically identify causal relationships between somatic genome alterations (SGAs) and differentially expressed genes (DEGs) for each TCGA HNSCC tumor using the tumor-specific causal inference (TCI) model. Then, we generalize the most statistically significant driver SGAs and their regulated DEGs in TCGA HNSCC cohort. Finally, we develop machine learning models that combine genomic and transcriptomic data to infer the protein functional activation states of driver SGAs in tumors, which enable us to represent a tumor in the space of cellular signaling systems. We discovered four mechanism-oriented subtypes of HNSCC, which show distinguished patterns of activation state of HNSCC driver proteins, and importantly, this subtyping is orthogonal to previously reported transcriptomic-based molecular subtyping of HNSCC. Further, our analysis revealed driver proteins that are likely involved in oncogenic processes induced by HPV infection, even though they are not perturbed by genomic alterations in HPV+ tumors.

Promising Biomarkers in Head and Neck Cancer: The Most Clinically Important miRNAs

Head and neck cancers (HNCs) comprise a heterogeneous group of tumors that extend from the oral cavity to the upper gastrointestinal tract. The principal etiologic factors for oral tumors include tobacco smoking and alcohol consumption, while human papillomavirus (HPV) infections have been accused of a high incidence of pharyngeal tumors. Accordingly, HPV detection has been extensively used to categorize carcinomas of the head and neck. The diverse nature of HNC highlights the necessity for novel, sensitive, and precise biomarkers for the prompt diagnosis of the disease, its successful monitoring, and the timely prognosis of patient clinical outcomes. In this context, the identification of certain microRNAs (miRNAs) and/or the detection of alterations in their expression patterns, in a variety of somatic fluids and tissues, could serve as valuable biomarkers for precision oncology. In the present review, we summarize some of the most frequently studied miRNAs (including miR-21, -375, -99, -34a, -200, -31, -125a/b, -196a/b, -9, -181a, -155, -146a, -23a, -16, -29, and let-7), their role as biomarkers, and their implication in HNC pathogenesis. Moreover, we designate the potential of given miRNAs and miRNA signatures as novel diagnostic and prognostic tools for successful patient stratification. Finally, we discuss the currently ongoing clinical trials that aim to identify the diagnostic, prognostic, or therapeutic utility of miRNAs in HNC.

An Eleven-microRNA Signature Related to Tumor-Associated Macrophages Predicts Prognosis of Breast Cancer

The dysregulation of microRNAs (miRNAs) has been known to play important roles in tumor development and progression. However, the understanding of the involvement of miRNAs in regulating tumor-associated macrophages (TAMs) and how these TAM-related miRNAs (TRMs) modulate cancer progression is still in its infancy. This study aims to explore the prognostic value of TRMs in breast cancer via the construction of a novel TRM signature. Potential TRMs were identified from the literature, and their prognostic value was evaluated using 1063 cases in The Cancer Genome Atlas Breast Cancer database. The TRM signature was further validated in the external Gene Expression Omnibus GSE22220 dataset. Gene sets enrichment analyses were performed to gain insight into the biological functions of this TRM signature. An eleven-TRM signature consisting of mir-21, mir-24-2, mir-125a, mir-221, mir-22, mir-501, mir-365b, mir-660, mir-146a, let-7b and mir-31 was constructed. This signature significantly differentiated the high-risk group from the low-risk in terms of overall survival (OS)/ distant-relapse free survival (DRFS) (p value < 0.001). The prognostic value of the signature was further enhanced by incorporating other independent prognostic factors in a nomogram-based prediction model, yielding the highest AUC of 0.79 (95% CI: 0.72−0.86) at 5-year OS. Enrichment analyses confirmed that the differentially expressed genes were mainly involved in immune-related pathways such as adaptive immune response, humoral immune response and Th1 and Th2 cell differentiation. This eleven-TRM signature has great potential as a prognostic factor for breast cancer patients besides unravelling the dysregulated immune pathways in high-risk breast cancer.

A risk score system based on a six-microRNA signature predicts the overall survival of patients with ovarian cancer

BACKGROUND

Ovarian cancer (OVC) is a devastating disease worldwide; therefore the identification of prognostic biomarkers is urgently needed. We aimed to determine a robust microRNA signature-based risk score system that could predict the overall survival (OS) of patients with OVC.

METHODS

We extracted the microRNA expression profiles and corresponding clinical data of 467 OVC patients from The Cancer Genome Atlas (TCGA) database and further divided this data into training, validation and complete cohorts. The key prognostic microRNAs for OVC were identified and evaluated by robust likelihood-based survival analysis (RLSA) and multivariable Cox regression. Time-dependent receiver operating characteristic (ROC) curves were then constructed to evaluate the prognostic performance of these microRNAs. A total of 172 ovarian cancer samples and 162 normal ovarian tissues were used to verify the credibility and accuracy of the selected markers of the TCGA cohort by quantitative real-time polymerase chain reaction (PCR).

RESULTS

We successfully established a risk score system based on a six-microRNA signature (hsa-miR-3074-5p, hsa-miR-758-3p, hsa-miR-877-5p, hsa-miR-760, hsa-miR-342-5p, and hsa-miR-6509-5p). This microRNA based system is able to characterize patients as either high or low risk. The OS of OVC patients, with either high or low risk, was significantly different when compared in the training cohort (p < 0.001), the validation cohort (p < 0.001) and the complete cohort (p < 0.001). Analysis of clinical samples further demonstrated that these microRNAs were aberrantly expressed in OVC tissues. The six-miRNA-based signature was correlated with the prognosis of OVC patients (p < 0.001).

CONCLUSIONS

The study established a novel risk score system that is predictive of patient prognosis and is a potentially useful guide for the personalized treatment of OVC patients.

A novel prognostic immunoscore based on The Cancer Genome Atlas to predict overall survival in colorectal cancer patients

Colorectal cancer (CRC) is highly prevalent worldwide. The relationship between the infiltration of immunocytes in CRC and clinical outcome has been investigated in recent years. The present study aims to construct a new prognostic signature using an immunocyte panel. Our novel prognostic immunoscore included 13 types of immunocytes, which were identified by least absolute shrinkage and selection operator (LASSO)-Cox regression. The time-dependent receiver operating characteristic (ROC) curve and Kaplan–Meier survival estimates were applied to evaluate the prognostic ability. Compared with the signature based on a single immune marker (i.e., CD8 mRNA expression and CD8⁺ expressing T cells), the novel prognostic immunoscore possessed better specificity and sensitivity of prognosis (area under the curves (AUCs) are 0.852, 0.856, and 0.774 for 1-, 2-, and 3-year survival times, respectively). Significant differences were identified between the high and low immunoscore groups in overall survival and disease-free survival in training and validation cohorts. Combining the immunoscore with clinical information may provide a more accurate prognosis for CRC. The immunoscore can identify patients with poor outcomes in the high Tumor Mutational Burden (TMB) group, who may benefit the most from immunotherapy. The immunoscore was also closely related to two immune checkpoints (i.e., PD-L1 and PD-1, r = 0.3087 and r = 0.3341, respectively). Collectively, our study demonstrates that the novel prognostic immunoscore reported here may be useful in distinguishing different prognoses and may improve the clinical management of patients with CRC.

3p Arm Loss and Survival in Head and Neck Cancer: An Analysis of TCGA Dataset

Loss of the 3p chromosome arm has previously been reported to be a biomarker of poorer outcome in both human papillomavirus (HPV)-positive and HPV-negative head and neck cancer. However, the precise operational measurement of 3p arm loss is unclear and the mutational profile associated with the event has not been thoroughly characterized. We downloaded the clinical, single nucleotide variation (SNV), copy number aberration (CNA), RNA sequencing, and reverse phase protein assay (RPPA) data from The Cancer Genome Atlas (TCGA) and The Cancer Proteome Atlas HNSCC cohorts. Survival data and hypoxia scores were downloaded from published studies. In addition, we report the inclusion of an independent Memorial Sloan Kettering cohort. We assessed the frequency of loci deletions across the 3p arm separately in HPV-positive and -negative disease. We found that deletions on chromosome 3p were almost exclusively an all or none event in the HPV-negative cohort; patients either had <1% or >97% of the arm deleted. 3p arm loss, defined as >97% deletion in HPV-positive patients and >50% in HPV-negative patients, had no impact on survival (p > 0.05). However, HPV-negative tumors with 3p arm loss presented at a higher N-category and overall stage and developed more distant metastases (p < 0.05). They were enriched for SNVs in TP53, and depleted for point mutations in CASP8, HRAS, HLA-A, HUWE1, HLA-B, and COL22A1 (false discovery rate, FDR < 0.05). 3p arm loss was associated with CNAs across the whole genome (FDR < 0.1), and pathway analysis revealed low lymphoid-non-lymphoid cell interactions and cytokine signaling (FDR < 0.1). In the tumor microenvironment, 3p arm lost tumors had low immune cell infiltration (FDR < 0.1) and elevated hypoxia (FDR < 0.1). 3p arm lost tumors had lower abundance of proteins phospho-HER3 and ANXA1, and higher abundance of miRNAs hsa-miR-548k and hsa-miR-421, which were all associated with survival. There were no molecular differences by 3p arm status in HPV-positive patients, at least at our statistical power level. 3p arm loss is largely an all or none phenomenon in HPV-negative disease and does not predict poorer survival from the time of diagnosis in TCGA cohort. However, it produces tumors with distinct molecular characteristics and may represent a clinically useful biomarker to guide treatment decisions for HPV-negative patients.

A Novel TCGA-Validated, MiRNA-Based Signature for Prediction of Breast Cancer Prognosis and Survival

Breast cancer (BC) is the most common cancer affecting women and the leading cause of cancer-related deaths worldwide. Compelling evidence indicates that microRNAs (miRNAs) are inextricably involved in the development of cancer. Here, we constructed a novel model, based on miRNA-seq and clinical data downloaded from The Cancer Genome Atlas (TCGA). Data from a total of 962 patients were included in this study, and the relationships among their clinicopathological features, survival, and miRNA-seq expression levels were analyzed. Hsa-miR-186 and hsa-miR-361 were identified as internal reference miRNAs and used to normalize miRNA expression data. A five-miRNA signature, constructed using univariate and multivariate Cox regression, was significantly associated with disease-specific survival (DSS) of patients with BC. Kaplan–Meier (KM) and receiver operating characteristic (ROC) analyses were conducted to confirm the clinical significance of the five-miRNA signature. Finally, a nomogram was constructed based on the five-miRNA signature to evaluate its clinical value. Cox regression analysis revealed that a five-miRNA signature was significantly associated with DSS of patients with BC. KM analysis demonstrated that the signature could efficiently distinguish high- and low-risk patients. Moreover, ROC analysis showed that the five-miRNA signature exhibited high sensitivity and specificity in predicting the prognosis of patients with BC. Patients in the high-risk subgroup who received adjuvant chemotherapy had a significantly lower incidence of mortality than those who did not. A nomogram constructed based on the five-miRNA signature was effective in predicting 5-year DSS. This study presents a novel five-miRNA signature as a reliable prognostic tool to predict DSS and provide theoretical reference significance for individualized clinical decisions for patients with BC.

Identification of miR-203a, mir-10a, and miR-194 as predictors for risk of lymphovascular invasion in head and neck cancers

Lymphovascular invasion (LVI) is an important prognostic indicator of lymph node metastasis and disease aggressiveness but clear molecular mechanisms mediating this in head and neck cancers (HNSC) remain undefined. To identify important microRNAs (miRNAs) in HNSC that associate with and are also predictive of increased risk of LVI, we used a combination of clustering algorithms, multiple regression analyses and machine learning approaches and analyzed miRNA expression profiles in the TCGA HNSC database. As the first step, we identified miRNAs with increased association with LVI as a binary variable. In order to determine whether the identified miRNAs would show functional clusters that are also indicative of increased risk for LVI, we carried out unsupervised as well as supervised clustering. Our results identified distinct clusters of miRNAs that are predictive of increased LVI. We further refined these findings using a Random forest approach, and miR-203a-3p, mir-10a-5p, and miR-194-5p to be most strongly associated with LVI. Pathway enrichment analysis showed these miRNAs targeted genes involved in Hippo signaling and fatty acid oxidation pathways that are mediators of lymph node metastasis. Specific association was also identified between the miRNAs associated with LVI and expression of several lymphangiogenic genes that could be critical for determination of therapeutic strategies.

Roles of microRNAs in Regulating Cancer Stemness in Head and Neck Cancers

Head and neck squamous cell carcinomas (HNSCCs) are epithelial malignancies with 5-year overall survival rates of approximately 40-50%. Emerging evidence indicates that a small population of cells in HNSCC patients, named cancer stem cells (CSCs), play vital roles in the processes of tumor initiation, progression, metastasis, immune evasion, chemo-/radioresistance, and recurrence. The acquisition of stem-like properties of cancer cells further provides cellular plasticity for stress adaptation and contributes to therapeutic resistance, resulting in a worse clinical outcome. Thus, targeting cancer stemness is fundamental for cancer treatment. MicroRNAs (miRNAs) are known to regulate stem cell features in the development and tissue regeneration through a miRNA-target interactive network. In HNSCCs, miRNAs act as tumor suppressors and/or oncogenes to modulate cancer stemness and therapeutic efficacy by regulating the CSC-specific tumor microenvironment (TME) and signaling pathways, such as epithelial-to-mesenchymal transition (EMT), Wnt/β-catenin signaling, and epidermal growth factor receptor (EGFR) or insulin-like growth factor 1 receptor (IGF1R) signaling pathways. Owing to a deeper understanding of disease-relevant miRNAs and advances in in vivo delivery systems, the administration of miRNA-based therapeutics is feasible and safe in humans, with encouraging efficacy results in early-phase clinical trials. In this review, we summarize the present findings to better understand the mechanical actions of miRNAs in maintaining CSCs and acquiring the stem-like features of cancer cells during HNSCC pathogenesis.

LINC01232 Sponges Multiple miRNAs and Its Clinical Significance in Pancreatic Adenocarcinoma Diagnosis and Prognosis

Background:

Long noncoding RNAs have been demonstrated to play important roles in different kinds of human malignancy. The purpose of this study was to evaluate the diagnostic and prognostic value of long intergenic non-protein coding RNA 1232 (LINC01232) in patients with pancreatic adenocarcinoma (PAAD) and further explore the clinical significance of the potential miRNAs that might be sponged by LINC01232.

Methods:

The potential target miRNAs that might be sponged by LINC01232 were analyzed using bioinformatics analysis. The Real-Time quantitative PCR was adopted to measure the relative expression of LINC01232 and target miRNAs in PAAD serum and tissue samples. The diagnostic and prognostic value of LINC01232 was evaluated using the receiver operating characteristic analysis and Kaplan-Meier survival analysis, respectively.

Results:

LINC01232 expression was upregulated in PAAD serum and tissues and associated with patients’ TNM stage. Serum LINC01232 expression had diagnostic value, and the high levels of LINC01232 could predict unfavorable prognosis in PAAD patients. miR-204-5p, miR-370-5p and miR-654-3p were proposed as 3 targets of LINC01232 in PAAD, and their decreased expression levels in PAAD patients showed certain clinical significance in diagnosis and prognosis.

Conclusion:

The data of this study revealed that LINC01232 expression is upregulated in PAAD serum and tissue samples with considerable diagnostic and prognostic significance. In addition, miR-204-5p, miR-370-5p and miR-654-3p may be sponged by LINC01232 in PAAD, which also show potencies in PAAD diagnosis and prognosis.

Construction of a Five-Super-Enhancer-Associated-Genes Prognostic Model for Osteosarcoma Patients

Osteosarcoma is a malignant tumor most commonly arising in children and adolescents and associated with poor prognosis. In recent years, some prognostic models have been constructed to assist clinicians in the treatment of osteosarcoma. However, the prognosis and treatment of patients with osteosarcoma remain unsatisfactory. Notably, super-enhancer (SE)-associated genes strongly promote the progression of osteosarcoma. In the present study, we constructed a novel effective prognostic model using SE-associated genes from osteosarcoma. Five SE-associated genes were initially screened through the least absolute shrinkage and selection operator (Lasso) penalized Cox regression, as well as univariate and multivariate Cox regression analyses. Meanwhile, a risk score model was constructed using the expression of these five genes. The excellent performance of the five-SE-associated-gene-based prognostic model was determined via time-dependent receiver operating characteristic (ROC) curves and Kaplan-Meier curves. Inferior outcome of overall survival (OS) was predicted in the high-risk group. A nomogram based on the polygenic risk score model was further established to validate the performance of the prognostic model. It showed that our prognostic model performed outstandingly in predicting 1-, 3-, and 5-year OS of patients with osteosarcoma. Meanwhile, these five genes also belonged to the hub genes associated with survival and necrosis of osteosarcoma according to the result of weighted gene co-expression network analysis based on the dataset of GSE39058. Therefore, we believe that the five-SE-associated-gene-based prognostic model established in this study can accurately predict the prognosis of patients with osteosarcoma and effectively assist clinicians in treating osteosarcoma in the future.

The Pre-Treatment C-Reactive Protein Represents a Prognostic Factor in Patients with Oral and Oropharyngeal Cancer Treated with Radiotherapy

The purpose of the present study was to evaluate the prognostic significance of the pre- treatment C-reactive protein (CRP) level in a cohort of 503 patients with oral and oropharyngeal cancer treated at a tertiary academic center between 2000 and 2017. Cancer-specific survival (CSS), overall survival (OS) and loco-regional control (LC) were calculated using Kaplan-Meier analysis. To evaluate the prognostic value of the CRP level for the clinical endpoints, univariate and multivariate Cox regression models were applied. The median follow-up period was 61 months. Patients were divided into elevated CRP (≥5 mg/L) and normal CRP groups, according to pre-treatment plasma levels. An increased CRP level was significantly associated with shorter CSS (p < 0.001, log-rank test), as well as with shorter OS (p < 0.001, log-rank test) and loco-regional control (p = 0.001, log-rank test). In addition, multivariate analysis identified CRP as an independent predictor for CSS (hazard ratio (HR) 1.59, 95% confidence interval (CI) 1.08-2.35; p = 0.020) as well as for OS (HR 1.62, 95%CI 1.17-2.24; p = 0.004) and LC (HR 1.50, 95%CI 1.06-2.14; p = 0.023). In subgroup analysis, Kaplan Meier curves revealed that an elevated pre-treatment CRP level was a consistent prognostic factor for poor CSS (p = 0.003, log-rank test), OS (p = 0.001, log-rank test), and LC (p = 0.028, log-rank test) in patients treated with definitive (chemo-) radiotherapy, whereas a significant association in patients undergoing surgery and postoperative radiotherapy was not detected. The pre-treatment CRP level seems to represent a prognostic factor for CSS, OS, and LC in patients with oral and oropharyngeal cancer, particularly in those treated with definitive (chemo-) radiotherapy. Additional large-scale prospective studies are warranted to confirm and extend our findings.