KCNN4 and S100A14 act as predictors of recurrence in optimally debulked patients with serous ovarian cancer

A diagnostic miRNA panel to detect recurrence of ovarian cancer through artificial intelligence approaches

BACKGROUND

Ovarian Cancer (OC) is the deadliest gynecology malignancy, whose high recurrence rate in OC patients is a challenging object. Therefore, having deep insights into the genetic and molecular mechanisms of OC recurrence can improve the target therapeutic procedures. This study aimed to discover crucial miRNAs for the detection of tumor recurrence in OC by artificial intelligence approaches.

METHOD

Through the ANOVA feature selection method, we selected 100 candidate miRNAs among 588 miRNAs. For their classification, a deep-learning model was employed to validate the significance of the candidate miRNAs. The accuracy, F1-score (high-risk), and AUC-ROC of classification test data based on the 100 miRNAs were 73%, 0.81, and 0.65, respectively. Association rule mining was used to discover hidden relations among the selected miRNAs.

RESULT

Five miRNAs, including miR-1914, miR-203, miR-135a-2, miR-149, and miR-9-1, were identified as the most frequent items among high-risk association rules. The identified miRNAs may target genes/proteins involved in epithelial-mesenchymal transition (EMT), resistance to therapy, and cancer stem cells; being responsible for the heterogeneity and plasticity of the tumor. Our conclusion presents mir-1914 as the significant candidate miRNA and the most frequent item. Current knowledge indicates that the dysregulated miR-1914 may function as a tumor suppressor or oncogene in the development of cancer.

CONCLUSION

These candidate miRNAs can be considered a powerful tool in the diagnosis of OC recurrence. We hypothesize that mir-1914 might open a new line of research in the realm of managing the recurrence of OC and could be a significant factor in triggering OC recurrence.

A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer

Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to identify a set of molecular markers for predicting platinum sensitivity. A signature predicting cisplatin sensitivity was generated using the Genomics of Drug Sensitivity in Cancer and The Cancer Genome Atlas databases. Four potential biomarkers (CYTH3, GALNT3, S100A14, and ERI1) were identified and optimized for immunohistochemistry (IHC). Validation was performed on a cohort of patients (n = 50) treated with surgical resection followed by adjuvant carboplatin. Predictive models were established to predict chemosensitivity. The four biomarkers were also assessed for their ability to prognosticate overall survival in three ovarian cancer microarray expression datasets from The Gene Expression Omnibus. The extreme gradient boosting (XGBoost) algorithm was selected for the final model to validate the accuracy in an independent validation dataset (n = 10). CYTH3 and S100A14, followed by nodal stage, were the features with the greatest importance. The four gene signature had comparable prognostication as clinical information for two-year survival. Assessment of tumour biology by means of gene expression can serve as an adjunct for prediction of chemosensitivity and prognostication. Potentially, the assessment of molecular markers alongside clinical information offers a chance to further optimise therapeutic decision making.

Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer

BACKGROUND

Ovarian cancer is one of the most common malignancies often resulting in a poor prognosis. 5-methylcytosine (m5C) is a common epigenetic modification with roles in eukaryotes. However, the expression and function of m5C regulatory factors in ovarian cancer remained unclear.

RESULTS

Two molecular subtypes with different prognostic and clinicopathological features were identified based on m5C regulatory factors. Meanwhile, functional annotation showed that in the two subtypes, 452 differentially expressed genes were significantly related to the malignant progression of ovarian cancer. Subsequently, four m5C genes were screened to construct a risk marker predictive of overall survival and indicative of clinicopathological features of ovarian cancer, also the robustness of the risk marker was verified in external dataset and internal validation set. multifactorial cox regression analysis and nomogram demonstrated that risk score was an independent prognostic factor for ovarian cancer prognosis.

CONCLUSION

In conclusion, our results revealed that m5C-related genes play a critical role in tumor progression in ovarian cancer. Further detection of m5C methylation could provide a novel targeted therapy for treating ovarian cancer.

Research Progress in Prognostic Factors and Biomarkers of Ovarian Cancer

Ovarian cancer is a serious threat to women's health; its early diagnosis rate is low and prone to metastasis and recurrence. The current conventional treatment for ovarian cancer is a combination of platinum and paclitaxel chemotherapy based on surgery. The recurrence and progression of ovarian cancer with poor prognosis is a major challenge in treatment. With rapid advances in technology, understanding of the molecular pathways involved in ovarian cancer recurrence and progression has increased, biomarker-guided treatment options can greatly improve the prognosis of patients. This review systematically discusses and summarizes existing and new information on prognostic factors and biomarkers of ovarian cancer, which is expected to improve the clinical management of patients and lead to effective personalized treatment.

S100A14 inhibits cell growth and epithelial-mesenchymal transition (EMT) in prostate cancer through FAT1-mediated Hippo signaling pathway

Prostate cancer (PCA) is an epithelial malignant tumor occurring in the prostate gland. It is the second most common male cancer in the world and one of the top five cancer deaths in men. To combat this disease, it is needed to identify important tumor suppressor genes and elucidate the molecular mechanisms. S100 calcium-binding protein A14 (S100A14), a member of the S100 family, is located on chromosome 1q21.3 and contains an EF-hand motif that binds calcium. S100A14 is involved in a variety of tumor biological processes in several types of cancers. Its expression level and related biological functions are tissue or tumor specific. However, its possible effects on prostate cancer are still unclear. Herein, we found the low expression of S100A14 in human prostate cancer tissues and cell lines. S100A14 suppressed the proliferation of prostate cancer cells and promoted cell apoptosis. Additionally, S100A14 suppressed the motility and EMT processes of prostate cancer cells. We further found S100A14 promoted the expression of FAT1 and activated the Hippo pathway, which, therefore, suppressed the prostate cancer progression. The in vivo assays confirmed that S100A14 suppressed tumor growth of prostate cancer cells through FAT1-mediated Hippo pathway in mice. In conclusion, we clarified the mechanism underlying S100A14 suppressing prostate cancer progression and, therefore, we thought S100A14 could serve as a tumor suppressor protein.

Ion Channels Orchestrate Pancreatic Ductal Adenocarcinoma Progression and Therapy

Pancreatic ductal adenocarcinoma is a devastating disease with a dismal prognosis. Therapeutic interventions are largely ineffective. A better understanding of the pathophysiology is required. Ion channels contribute substantially to the "hallmarks of cancer." Their expression is dysregulated in cancer, and they are "misused" to drive cancer progression, but the underlying mechanisms are unclear. Ion channels are located in the cell membrane at the interface between the intracellular and extracellular space. They sense and modify the tumor microenvironment which in itself is a driver of PDAC aggressiveness. Ion channels detect, for example, locally altered proton and electrolyte concentrations or mechanical stimuli and transduce signals triggered by these microenvironmental cues through association with intracellular signaling cascades. While these concepts have been firmly established for other cancers, evidence has emerged only recently that ion channels are drivers of PDAC aggressiveness. Particularly, they appear to contribute to two of the characteristic PDAC features: the massive fibrosis of the tumor stroma (desmoplasia) and the efficient immune evasion. Our critical review of the literature clearly shows that there is still a remarkable lack of knowledge with respect to the contribution of ion channels to these two typical PDAC properties. Yet, we can draw parallels from ion channel research in other fibrotic and inflammatory diseases. Evidence is accumulating that pancreatic stellate cells express the same "profibrotic" ion channels. Similarly, it is at least in part known which major ion channels are expressed in those innate and adaptive immune cells that populate the PDAC microenvironment. We explore potential therapeutic avenues derived thereof. Since drugs targeting PDAC-relevant ion channels are already in clinical use, we propose to repurpose those in PDAC. The quest for ion channel targets is both motivated and complicated by the fact that some of the relevant channels, for example, KCa3.1, are functionally expressed in the cancer, stroma, and immune cells. Only in vivo studies will reveal which arm of the balance we should put our weights on when developing channel-targeting PDAC therapies. The time is up to explore the efficacy of ion channel targeting in (transgenic) murine PDAC models before launching clinical trials with repurposed drugs.

KCNN4 induces multiple chemoresistance in breast cancer by regulating BCL2A1

Multidrug chemoresistance is a major clinical obstacle in breast cancer treatment. We aimed to elucidate the sensitivity to therapeutics in gemcitabine-resistant breast cancer models. Pooled library screening combined with RNA-seq was conducted to explore the potential targets involved in gemcitabine resistance in breast cancer cells. Cytotoxicity and tumor xenograft assays were used to evaluate the effect of calcium-activated channel subfamily N member 4 (KCNN4) inhibitors on the cellular sensitivity of breast cancer cells to chemotherapeutic drugs both in vitro and in vivo. We found that KCNN4 is an important determinant for the cytotoxicity of gemcitabine. Elevated KCNN4 expression enhanced resistance to chemotherapeutic antimetabolites and promoted cell proliferation. Conversely, silencing KCNN4 or chemical inhibition of KCNN4 by the specific inhibitor TRAM-34 inhibited the chemoresistance and cell proliferation. Mechanistically, KCNN4 upregulated BCL2-related protein A1 (BCL2A1) to suppress apoptosis by activating RAS-MAPK and PI3K-AKT signaling. Moreover, high expression levels of KCNN4 and BCL2A1 were associated with shortened disease-free survival in the cohort studies. Collectively, our findings showed that KCNN4 is a key modulator of progression and drug resistance in breast cancer, indicating that targeting KCNN4 may serve as a promising therapeutic strategy to overcome multidrug chemoresistance in this disease.

Development of a Cell-Based Assay for Identifying KCa3.1 Inhibitors Using Intestinal Epithelial Cell Lines

Inhibition of the K_Ca3.1 potassium channel has therapeutic potential in a variety of human diseases, including inflammation-associated disorders and cancers. However, K_Ca3.1 inhibitors with high therapeutic promise are currently not available. This study aimed to establish a screening assay for identifying inhibitors of K_Ca3.1 in native cells and from library compounds derived from natural products in Thailand. The screening platform was successfully developed based on a thallium flux assay in intestinal epithelial (T84) cells with a Z' factor of 0.52. The screening of 1352 compounds and functional validation using electrophysiological analyses identified 8 compounds as novel K_Ca3.1 inhibitors with IC₅₀ values ranging from 0.14 to 6.57 µM. These results indicate that the assay developed is of excellent quality for high-throughput screening and capable of identifying K_Ca3.1 inhibitors. This assay may be useful in identifying novel K_Ca3.1 inhibitors that may have therapeutic potential for inflammation-associated disorders and cancers.

Proteomic analysis enables distinction of early- versus advanced-stage lung adenocarcinomas

Background

A gel‐free proteomic approach was utilized to perform in‐depth tissue protein profiling of lung adenocarcinoma (ADC) and normal lung tissues from early and advanced stages of the disease. The long‐term goal of this study is to generate a large‐scale, label‐free proteomics dataset from histologically well‐classified lung ADC that can be used to increase further our understanding of disease progression and aid in identifying novel biomarkers.

Methods and results

Cases of early‐stage (I‐II) and advanced‐stage (III‐IV) lung ADCs were selected and paired with normal lung tissues from 22 patients. The histologically and clinically stratified human primary lung ADCs were analyzed by liquid chromatography‐tandem mass spectrometry. From the analysis of ADC and normal specimens, 4863 protein groups were identified. To examine the protein expression profile of ADC, a peak area‐based quantitation method was used. In early‐ and advanced‐stage ADC, 365 and 366 proteins were differentially expressed, respectively, between normal and tumor tissues (adjusted P‐value < .01, fold change ≥ 4). A total of 155 proteins were dysregulated between early‐ and advanced‐stage ADCs and 18 were suggested as early‐specific stage ADC. In silico functional analysis of the upregulated proteins in both tumor groups revealed that most of the enriched pathways are involved in mRNA metabolism. Furthermore, the most overrepresented pathways in the proteins that were unique to ADC are related to mRNA metabolic processes.

Conclusions

Further analysis of these data may provide an insight into the molecular pathways involved in disease etiology and may lead to the identification of biomarker candidates and potential targets for therapy. Our study provides potential diagnostic biomarkers for lung ADC and novel stage‐specific drug targets for rational intervention.

A Clinicopathological Analysis of S100A14 Expression in Colorectal Cancer

BACKGROUND/AIM

The calcium-binding protein S100A14 is involved in processes related to tumorigenesis and tumor propagation, such as proliferation, apoptosis, motility and invasiveness. Our aim was to investigate its role in colorectal cancer.

PATIENTS AND METHODS

One hundred and seven patients (65 men and 42 women) were included in this study. They had been diagnosed with colorectal cancer and undergone complete resection of their primary tumor. Tissue samples from archival blocks of their normal and malignant colorectal tissues were used for immunohistochemical assessment of S100A14 expression. S100A14 levels were evaluated using image analysis and associated with various clinicopathological parameters and prognosis.

RESULTS

S100A14 expression was reduced in malignant tissues when compared to normal intestinal mucosa in cases of T3-T4 tumors (p=0.017). Moreover, as far as S100A14 levels in malignant tissues are concerned, they were lower in T3-T4 tumors (p=0.001), N2 disease (p=0.034) and M1 disease (p=0.019). Finally, very high S100A14 production (>75^th percentile) was associated with shorter disease-specific (HR=3.584, p=0.045) and relapse-free survival (HR=4.527, p=0.007) in multivariate survival analysis.

CONCLUSION

S100A14 expression is decreased in advanced colorectal cancer. However, cases with very high S100A14 levels have a worse survival.

Loss of S100A14 expression at the tumor-invading front correlates with poor differentiation and worse prognosis in oral squamous cell carcinoma

BACKGROUND

We previously showed a tumor-suppressive function of S100A14 in oral squamous cell carcinoma (OSCC). This study aimed to examine the prognostic significance and differentiation-related function of S100A14 in OSCC.

METHODS

S100A14 expression was examined in 170 OSCCs from Norwegian and Nepalese populations using immunohistochemistry. Pro-differentiation function was investigated by overexpressing and silencing S100A14 expression in OSCC-derived cells. External transcriptomic datasets were used to validate association between S100A14 and differentiation markers in OSCC.

RESULT

Loss of S100A14 expression at the invading tumor fronts significantly correlated with poor differentiation and reduced 10-years survival of OSCC-patients. Multivariate Cox analysis identified S100A14 to be an independent prognostic factor. Modulation of S100A14 expression in OSCC-derived cells positively correlated with the expression of differentiation markers. Analysis of external datasets supported the pro-differentiation function of S100A14.

CONCLUSION

These results indicate that S100A14 is a pro-differentiation protein and its expression might be useful as a prognostic marker in OSCC.

Recurrence-Associated Multi-RNA Signature to Predict Disease-Free Survival for Ovarian Cancer Patients

Ovarian cancer (OvCa) is an intractable gynecological malignancy due to the high recurrence rate. Several molecular biomarkers have been previously screened for early identifying patients with a high recurrence risk and poor prognosis. However, all the known studies focused on a single type of RNAs, not integrating various types. This study was to construct a new multi-RNA-based model to predict the recurrence and prognosis for OvCa patients by using the messenger RNA (mRNA, including long noncoding RNA (lncRNA)) and microRNA (miRNA) sequencing data of The Cancer Genome Atlas database. After univariate Cox regression and least absolute shrinkage and selection operator analyses, a multi-RNA-based signature (2 miRNAs: hsa-miR-508, hsa-miR-506; 1 lncRNA: TM4SF1-AS1; 11 mRNAs: MAGI3, SLAMF7, GLI2, PDK1, ARID3A, PLEKHG4B, TNFAIP8L3, C1QTNF3, NDUFAF1, CH25H, TMEM129) was generated and used to establish a risk score model. The high- and low-risk patients classified by the median risk score exhibited significantly different recurrence risks (89% versus 61%, p < 0.001) and survival time (the area under the receiver operating characteristic curve (AUC) = 0.901 for 5-year disease-free survival (DFS)). This risk model was independent of other clinical features and superior to pathologic staging for DFS prediction (AUC, 0.906 versus 0.524; C-index, 0.633 versus 0.510). Furthermore, some new interaction axes were revealed to explain the possible functions of these RNAs (competing endogenous RNA: TM4SF1-AS1-miR-186-STEAP2, LINC00536-miR-508-STEAP2, LINC00475-miR-506-TMEM129; coexpression: LINC00598-PLEKHG4B). In conclusion, this multi-RNA-based risk model may be clinically useful to stratify OvCa patients with different recurrence risks and survival outcomes and included RNAs may be potential therapeutic targets.

KCa3.1 Channels Confer Radioresistance to Breast Cancer Cells

K_Ca3.1 K⁺ channels reportedly contribute to the proliferation of breast tumor cells and may serve pro-tumor functions in the microenvironment. The putative interaction of K_Ca3.1 with major anti-cancer treatment strategies, which are based on cytotoxic drugs or radiotherapy, remains largely unexplored. We employed K_Ca3.1-proficient and -deficient breast cancer cells derived from breast cancer-prone MMTV-PyMT mice, pharmacological K_Ca3.1 inhibition, and a syngeneic orthotopic mouse model to study the relevance of functional K_Ca3.1 for therapy response. The K_Ca3.1 status of MMTV-PyMT cells did not determine tumor cell proliferation after treatment with different concentrations of docetaxel, doxorubicin, 5-fluorouracil, or cyclophosphamide. K_Ca3.1 activation by ionizing radiation (IR) in breast tumor cells in vitro, however, enhanced radioresistance, probably via an involvement of the channel in IR-stimulated Ca²⁺ signals and DNA repair pathways. Consistently, K_Ca3.1 knockout increased survival time of wildtype mice upon syngeneic orthotopic transplantation of MMTV-PyMT tumors followed by fractionated radiotherapy. Combined, our results imply that K_Ca3.1 confers resistance to radio- but not to chemotherapy in the MMTV-PyMT breast cancer model. Since K_Ca3.1 is druggable, K_Ca3.1 targeting concomitant to radiotherapy seems to be a promising strategy to radiosensitize breast tumors.

KCNN4 promotes invasion and metastasis through the MAPK/ERK pathway in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is one of the most common malignancies in the world, and is well-known for its bad prognosis. Potassium calcium-activated channel subfamily N member 4 (KCNN4) is a type of intermediate conductance calcium-activated potassium channel, and increasing evidence suggests that KCNN4 contributes to the regulation of invasion and metastasis in a number of cancers. However, its clinical significance and biological function remain unclear in the HCC disease process. In this study, the expression levels of KCNN4 in 86 HCC samples were compared with corresponding paracancerous tissues. sh-RNA was used to reduce the expression of KCNN4 in Hep3B HCC cells in vitro; this was confirmed by Real time-PCR and western blotting. Wound healing, transwell assays and high content analysis were performed to investigate the tumor-promoting characteristics of KCNN4 in Hep3B HCC cells. As results, KCNN4 expression was significantly associated with preoperative serum alpha-fetoprotein level (p=0.038) and TNM stage (p=0.039). Additionally, patients with high KCNN4 amplification in HCC tissue exhibited shorter disease-free survival, whereas there was no statistical significance between KCNN4 amplification and overall survival. Wound healing and transwell assays showed that knockdown of KCNN4 expression could reduce migration and invasion abilities of HCC cells. High content analysis result showed that down-regulated KCNN4 could inhibit the ability of HCC cell proliferation. The mitogen-activated protein kinase (MAPK) pathway is active in cell proliferation, differentiation, migration, senescence, and apoptosis. Matrix metallopeptidase 9 and extracellular signal regulated kinase 1/2 (ERK1/2) were important biomarkers of MAPK/ERK pathway, knockdown of KCNN4 reduced the expression of MMP9 and ERK1/2. These findings showed that KCNN4 promotes HCC invasion and metastasis through the MAPK/ERK pathway.

Identification of S100A14 as a metastasis-promoting molecule in a murine organotropic metastasis model

Cancer metastasis shows great diversity in target organs, routes and molecular mechanisms depending on the type of cancer and even on the individual patients. To identify key molecules involved in metastasis, we constructed a murine model system including multiple sublines with different organotropism and pathways of metastasis. We selected metastatic sublines from a murine mammary tumor cell line MCH66. Using this model, we extracted metastasis-related molecules by gene expression screening methods and verified their metastasis-promoting effects by gene knockdown or overexpression experiments. For the candidates promoting metastasis, we analyzed molecular functions involved in metastasis: cell growth, motility and invasive activity. We established a metastasis model including low metastatic sublines (66C8, 66LM, 66-4) and highly metastatic counterparts with various organotropism, such as to the lung (66Lu10), liver (HM-KAN5) and general organs (66HM and its clones: HM1-6 and HM1-7). The sublines basically exhibited the invasion-independent metastasis pathway characterized by endothelial cell-covered tumor emboli, whereas 66HM and HM-KAN5 showed an alternative metastasis pathway based on invasion in part and in whole, respectively. Comprehensive gene analysis extracted several molecular candidates responsible for metastasis. S100A14 was identified as one of the promissing candidates promoting lung-metastasis, which was verified by gene knockdown experiments in vivo. In addition, in vivo and in vitro functional analyses demonstrated that S100A14 enhanced scattering, motility and invasiveness of mouse tumor cells. Our model system may be adaptable to the diversity of metastasis in human cancers and useful for exploring the molecular mechanism responsible for metastasis.

Prognostic and clinicopathological significance of S100A14 expression in cancer patients: A meta-analysis

BACKGROUND

The prognostic significance of S100A14 for survival of cancer patients remains controversial. Therefore, we conducted this meta-analysis to explore the association between S100A14 expression and cancer prognosis.

METHOD

Eligible studies were identified by searching the online databases Pubmed and EMBASE up to August 2018. Odds ratios (ORs) with 95% confidence intervals (CIs) severed as the summarized statistics for clinicopathological assessments and hazard ratios (HRs) with 95% CIs were calculated to clarify the correlation between S100A14 expression and prognosis of different cancers.

RESULTS

A total of 11 studies with 1651 cancer patients were enrolled. The results indicated that S100A14 expression was not significantly associated with overall survival (OS) in total various cancers (HR = 1.54, 95% CI:0.89-2.67, P = .121). Further subgroup analysis stratified by tumor type showed that elevated S100A14 expression was associated with poor OS in breast cancer (HR = 3.66, 95% CI: 1.75-7.62, P < .001) and in ovarian cancer patients (HR = 3.78, 95%CI: 1.63-8.73, P = .002). Interestingly, high S100A14 expression was correlated with poor tumor differentiation (OR = 2.51, 95% CI: 1.52-4.13, P < .001). However, there were no significant correlations between S100A14 expression and other clinicopathologic characteristics. Begg funnel plot and Egger test showed that no publication bias was detected.

CONCLUSIONS

Our meta-analysis suggests that S100A14 overexpression might be a predictive biomarker for poor prognosis in patients with breast cancer and ovarian cancer. Large-scale studies are required to confirm these results.

Lipid metabolism and Calcium signaling in epithelial ovarian cancer

Epithelial Ovarian cancer (EOC) is the deadliest gynecologic malignancy and represents the fifth leading cause of all cancer-related deaths in women. The majority of patients are diagnosed at an advanced stage of the disease that has spread beyond the ovaries to the peritoneum or to distant organs (stage FIGO III-IV) with a 5-year overall survival of about 29%. Consequently, it is necessary to understand the pathogenesis of this disease. Among the factors that contribute to cancer development, lipids and ion channels have been described to be associated to cancerous diseases particularly in breast, colorectal and prostate cancers. Here, we reviewed the literature data to determine how lipids or lipid metabolites may influence EOC risk or progression. We also highlighted the role and the expression of the calcium (Ca²⁺) and calcium-activated potassium (KCa) channels in EOC and how lipids might regulate them. Although lipids and some subclasses of nutritional lipids may be associated to EOC risk, lipid metabolism of LPA (lysophosphatidic acid) and AA (arachidonic acid) emerges as an important signaling network in EOC. Clinical data showed that they are found at high concentrations in EOC patients and in vitro and in vivo studies referred to them as triggers of the Ca²⁺entry in the cancer cells inducing their proliferation, migration or drug resistance. The cross-talk between lipid mediators and Ca²⁺ and/or KCa channels needs to be elucidated in EOC in order to facilitate the understanding of its outcomes and potentially suggest novel therapeutic strategies including treatment and prevention.

Expression profile and functional role of S100A14 in human cancer

S100A14 is one of the new members of the multi-functional S100 protein family. Expression of S100A14 is highly heterogeneous among normal human tissues, suggesting that the regulation of S100A14 expression and its function may be tissue- and context-specific. Compared to the normal counterparts, S100A14 mRNA and protein levels have been found to be deregulated in several cancer types, indicating a functional link between S100A14 and malignancies. Accordingly, S100A14 is functionally linked with a number of key signaling molecules such as p53, p21, MMP1, MMP9, MMP13, RAGE, NF-kB, JunB, actin and HER2. Of interest, S100A14 seems to have seemingly opposite functions in malignancies arising from the gastrointestional tract (tissues rich in epithelial components) compared to cancers in the other parts of the body (tissues rich in mesenchymal components). The underlying mechanism for these observations are currently unclear and may be related to the relative abundance and differences in the type of interaction partners (effector protein) in different cancer types and tissues. In addition, several studies indicate that the expression pattern of S100A14 has a potential to be clinically useful as prognostic biomarker in several cancer types. This review attempts to provide a comprehensive summary on the expression pattern and functional roles/related molecular pathways in different cancer types. Additionally, the prognostic potential of S100A14 in the management of human malignancies will be discussed.

Prognostic values of S100 family members in ovarian cancer patients

Objective

Exhibiting high consistence in sequence and structure, S100 family members are interchangeable in function and they show a wide spectrum of biological processes, including proliferation, apoptosis, migration, inflammation and differentiation and the like. While the prognostic value of each individual S100 in ovarian cancer is still elusive. In current study, we investigated the prognostic value of S100 family members in the ovarian cancer.

Methods

We used the Kaplan Meier plotter (KM plotter) database, in which updated gene expression data and survival information are from 1657 ovarian cancer patients, to assess the relevance of individual S100 family mRNA expression to overall survival in various ovarian cancer subtypes and different clinicopathological features.

Results

It was found that high expression of S100A2 (HR = 1.18, 95%CI: 1.04–1.34, P = 0.012), S100A7A (HR = 1.3, 95%CI: 1.04–1.63, P = 0.02),S100A10 (HR = 1.2, 95%CI: 1.05–1.38, P = 0.0087),and S100A16 (HR = 1.23, 95%CI: 1–1.51, P = 0.052) were significantly correlated with worse OS in all ovarian cancer patients, while the expression of S100A1 (HR = 0.87, 95%CI: 0.77–0.99, P = 0.039), S100A3 (HR = 0.83, 95%CI: 0.71–0.96, P = 0.0011), S100A5 (HR = 0.84, 95%CI: 0.73–0.97, P = 0.017), S100A6 (HR = 0.84, 95%CI: 0.72–0.98, P = 0.024), S100A13 (HR = 0.85, 95%CI:0.75–0.97, P = 0.014) and S100G (HR = 0.86, 95%CI: 0.74–0.99, P = 0.041) were associated with better prognosis. Furthermore, we assessed the prognostic value of S100 expression in different subtypes and the clinicopathological features, including pathological grades, clinical stages and TP53 mutation status, of ovarian cancer patients.

Conclusion

Comprehensive understanding of the S100 family members may have guiding significance for the diagnosis and outcome of ovarian cancer patients.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5170-3) contains supplementary material, which is available to authorized users.

Identification of pathway-based recurrence-associated signatures in optimally debulked patients with serous ovarian cancer

Serous ovarian cancer (SOC) is the most common form of the histological subtype of epithelial ovarian cancer, with the worst clinical outcome. Despite improvements in surgery and chemotherapy, most patients with SOC experience recurrence within 12-18 months of first-line treatment. Current studies are unable to robustly predict the recurrence of SOC, and more accurate predictive models are urgently required. We have, therefore, developed a novel pathway-structured model to predict the recurrence of SOC. We trained the model on a set of 333 patients and validated it in 3 diversified validation datasets of 403 patients. Genes significantly associated with recurrence within each pathway were identified using a Cox proportional hazards model based on LASSO estimation in the training dataset. Next, a pathway-structured scoring matrix was obtained after computation of the prognostic score for each pathway by fitting to the Cox proportional hazards model. With the pathway-structure scoring matrix as an input, the pathway-based recurrent signatures were identified using the Cox proportional hazards model based on LASSO estimation and the significant pathway-based signatures were externally validated in 3 independent datasets. Meanwhile, our pathway-structured model was compared with a commonly used gene-based model. Our results revealed that our 12 pathway-based signatures successfully predicted the recurrence of SOC with high accuracy in the training dataset and in the 3 validation datasets. Moreover, our pathway-structured model was superior to the gene-based model in 4 datasets. The pathways selected in our study will provide new insights into the pathogenesis and clinical treatments of SOC.

Overexpression of S100A14 contributes to malignant progression and predicts poor prognosis of lung adenocarcinoma

BACKGROUND

S100A14 is a member of the S100 calcium-binding protein family that exerts important phenotypic effects on cell proliferation, apoptosis, differentiation, and motility. However, the functional role and potential clinical significance of S100A14 in lung adenocarcinoma has not yet been clarified.

METHODS

We analyzed genomic alterations of S100A14 using The Cancer Genome Atlas lung adenocarcinoma genomic dataset. S100A14 displayed significant copy number amplification in lung adenocarcinoma. We detected S100A14 expression in lung adenocarcinoma and analyzed the correlation between S100A14 expression and clinicopathological characteristics.

RESULTS

Immunohistochemical analysis showed that S100A14 expression was obviously upregulated in lung adenocarcinoma tissues compared to matched normal counterparts. Statistical analysis revealed that S100A14 expression strongly correlated with poor differentiation, metastasis, stage, smoking, and EGFR mutation. Furthermore, our data indicated that S100A14 serum levels were higher in lung adenocarcinoma patients than healthy controls. Intriguingly, S100A14 serum levels were related to distant metastasis (P = 0.028). High S100A14 expression was significantly associated with overall (P = 0.0016) and post progression (P = 0.039) survival. In addition, we investigated the biological functions of S100A14 in lung adenocarcinoma cell lines. The results demonstrated that S100A14 promoted cell migration and invasion of SPCA1 and Glc-82 cells.

CONCLUSIONS

S100A14 increases the motility of lung adenocarcinoma cells, and might be a diagnostic and prognostic serum biomarker and potential therapeutic target for lung adenocarcinoma.

The role of the long non-coding RNA TDRG1 in epithelial ovarian carcinoma tumorigenesis and progression through miR-93/RhoC pathway

As one of the most frequently diagnosed cancers in women, the development and progression of epithelial ovarian carcinoma (EOC) remains an open area of research. The role of long non-coding RNAs (lncRNAs) in EOC is an emerging field of study. We found that LncRNA TDRG1 (human testis development-related gene 1) was highly expressed in EOC tissues than in normal ovarian tissues, and expression differed significantly with differentiation. LncRNA TDRG1 downregulation suppressed EOC cell proliferation, migration, and invasion, while its overexpression had the opposite effect. Bioinformatic predictions and dual-luciferase reporter assays showed that LncRNA TDRG1 has possible miRNA-93 (miR-93) binding sites. LncRNA TDRG1 downregulation upregulated miR-93 expression, while its overexpression reduced miR-93 expression. In addition, TDRG1 downregulation reduced the expression of Ras homolog gene family member C (RhoC), P70 ribosomal S6 kinase (P70S6 K), Bcl-xL, and matrix metalloproteinase 2 (MMP2) protein, which are regulated by miR-93, while its upregulation induced RhoC, P70S6 K, Bcl-xL, and MMP2 protein expression. In vivo, LncRNA TDRG1 overexpression induced tumor development and RhoC expression. Taken together, our results demonstrated for the first time that LncRNA TDRG1 may be a new and important diagnostic and therapeutic target in EOC.