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Aim: Cell invasion leading to metastasis is a major cause of treatment failure in head–neck cancers (HNCs). Identifying prognostic molecules associated with invasiveness is imperative for clinical applications. Materials & methods: A systemic approach was used to globally survey invasion-related genes, including transcriptomic profiling, pathway analysis, data mining and prognostic assessment using TCGA-HNSC dataset. Results: Six functional pathways and six hub molecules (LAMA3, LAMC2, THBS1, IGF1R, PDGFB and TGFβ1) were identified that significantly contributed to cell invasion, leading to poor survival in HNC patients. Combinations of multiple biomarkers substantially increased the probability of accurately predicting prognosis. Conclusion: Our six defined invasion-related molecules may be used as a panel signature in precision medicine for prognostic indicators or molecular therapeutic targets for HNC.

BackgroundPancreatic ductal adenocarcinoma (PDAC) is highly aggressive and has poor prognosis. There are few biomarkers to inform treatment decisions, and collecting tumor samples for genomic or drug sensitivity testing is challenging.MethodsCirculating tumor cells (CTCs) were prepared from the liquid biopsies of PDAC patients. These cells were subsequently expanded ex vivo to form CTC-derived organoid cultures, using a laboratory-developed biomimetic cell culture system. The CTC-derived organoids were tested for sensitivity to a PDAC panel of nine drugs, with tests conducted in triplicate, and a weighted cytotoxicity score (CTS) was calculated from the results. Clinical response to treatment in patients was evaluated using Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 criteria at the time of blood sampling and 3 months later. CTS was then correlated with clinical response, and analyzed using 2 × 2 contingency tables.ResultsA total of 41 liquid biopsies were collected from 31 patients, with 87.8% of liquid biopsies from patients with Stage 4 disease. CTC-derived organoid expansion was achieved in 3 weeks, with 87.8% culture efficiency. CTC-derived organoid cultures were positive for EpCAM staining and negative for CD45 staining in surface marker analysis. All patients had received a median of two lines of treatment prior to enrollment, and prospective utility analysis indicated significant correlation of CTS with clinical treatment response. Two representative case studies are also presented to illustrate the relevant clinical contexts.ConclusionsIn this study, CTCs were expanded from the liquid biopsies of PDAC patients with a high success rate. Drug sensitivity profiles from CTC-derived organoid cultures correlated meaningfully with treatment response. Further studies are warranted to validate the predictive potential for this approach.Trial RegistrationTaipei Medical University Hospital Protocol Record N201803020, registered on July 10, 2018; ClinicalTrials.gov Identifier: NCT04972461, retrospectively registered on July 22, 2021.

Chemotherapy resistance is a huge barrier for head and neck cancer (HNC) patients and therefore requires close attention to understand its underlay mechanisms for effective strategies. In this review, we first summarize the molecular mechanisms of chemotherapy resistance that occur during the treatment with cisplatin, 5-fluorouracil, and docetaxel/paclitaxel, including DNA/RNA damage repair, drug efflux, apoptosis inhibition, and epidermal growth factor receptor/focal adhesion kinase/nuclear factor-κB activation. Next, we describe the potential approaches to combining conventional therapies with previous cancer treatments such as immunotherapy, which may improve the treatment outcomes and prolong the survival of HNC patients. Overall, by parsing the reported molecular mechanisms of chemotherapy resistance within HNC patient’s tumors, we can improve the prediction of chemotherapeutic responsiveness, and reveal new therapeutic targets for the future.

Vascular leiomyosarcoma is an extremely rare tumor and is associated with poor prognosis among leiomyosarcoma. Surgical resection remains the main treatment option. But outcome of definitive treatment with chemoradiotherapy in inoperable patients is not clear. Here, we report treatment and outcome of definitive chemoradiotherapy in a case of vascular leiomyosarcoma. A 64-year-old man with the initial presentation of pulsatile right neck mass was diagnosed with right carotid body leiomyosarcoma. He refused surgical intervention due to risk of carotid body injury and ischemic stroke. Successful tumor control was achieved with carboplatin-based concurrent chemoradiotherapy. Investigational liquid biopsy for circulating sarcoma cells was also performed to analyze drug sensitivity profile of this rare tumor. One year after treatment, the disease remained well controlled and there was no evidence of baroreflex failure or treatment-related late toxicities. To our best knowledge, this is the first case report of right carotid body leiomyosarcoma controlled with definitive concurrent chemoradiotherapy. The approach of personalized multi-modality treatment will be a focus of our future investigation.

Simple Summary The conventional methods that seek to predict clinical treatment response are based on the number of circulating tumor cells (CTCs) present in liquid biopsies or genetic profiling of extracted CTCs. This paper presents a novel process by which CTCs can be extracted from blood samples taken from head and neck cancer patients and then expanded ex vivo to form organoids that can be tested with a panel of anti-cancer treatments. The resulting drug sensitivity profiles derived from cisplatin treatment of organoids were subsequently found to correlate with clinical treatment response to cisplatin in patients. CTCs extracted from liquid biopsies for ex vivo expansion negates the need for complicated and potentially risky biopsies of tumor material, thereby supporting the application of this procedure for checkups and treatment monitoring. Abstract The advanced-stage head and neck cancer (HNC) patients respond poorly to platinum-based treatments. Thus, a reliable pretreatment method for evaluating platinum treatment response would improve therapeutic efficiency and outcomes. This study describes a novel strategy to predict clinical drug responses in HNC patients by using eSelect, a lab-developed biomimetic cell culture system, which enables us to perform ex vivo expansion and drug sensitivity profiling of circulating tumor cells (CTCs). Forty liquid biopsies were collected from HNC patients, and the CTCs were expanded ex vivo using the eSelect system within four weeks. Immunofluorescence staining confirmed that the CTC-derived organoids were positive for EpCAM and negative for CD45. Two illustrative cases present the potential of this strategy for evaluating treatment response. The statistical analysis confirmed that drug sensitivity in CTC-derived organoids was associated with a clinical response. The multivariant logistic regression model predicted that the treatment accuracy of chemotherapy responses achieved 93.75%, and the area under the curves (AUCs) of prediction models was 0.8841 in the whole dataset and 0.9167 in cisplatin specific dataset. In summary, cisplatin sensitivity profiles of patient-derived CTCs expanded ex vivo correlate with a clinical response to cisplatin treatment, and this can potentially underpin predictive assays to guide HNC treatments.

Circulating tumor cells (CTCs) can be used for the early detection of cancer and determination of the effectiveness of anticancer drug treatment. Sometimes CTC grows on a culture medium which has a honeycomb texture, and existing detection methods cannot achieve satisfactory results because the honeycomb textures are more salient than the CTCs edges. Thus, a CTCs extraction method for honeycomb textures from microscope images is needed.In this paper, we propose a new algorithm to remove honeycomb texture from microscope images. We confirmed that our proposed algorithm can sufficiently remove the honeycomb texture even the periodicity of the patterns are weak. Also our method achieves a high segmentation accuracy for images where the background is more salient than the CTCs edges.

In commerce, businesses use branding to differentiate their product and service offerings from those of their competitors. The brand incorporates a set of product or service features that are assoc...

Small cell lung cancer (SCLC) represents one of the most aggressive malignancies among cancer types. Not only tumor sample availability is limited, but also the ability for tumor cells to rapidly acquire drug resistance are the rate-limiting bottlenecks for overall survival in current clinical settings. A liquid biopsy capable of capturing and enriching circulating tumor cells (CTCs), together with the possibility of drug screening, is a promising solution. Here, we illustrate the development of a highly efficient ex vivo CTC expansion system based on binary colloidal crystals substrate. Clinical samples were enrolled from 22 patients with SCLC in the study. The CTCs were enriched and expanded from the collected peripheral blood samples. Expanded cells were analyzed for protein expression and observed for drug sensitivity with the use of immunofluorescence and ATP titer evaluation, respectively. Successful CTC spheroid proliferation was established after 4 weeks within 82% of all the collected peripheral blood samples from enrolled patients. Upon immunofluorescence analysis, the enriched cells showed positive markers for EpCAM, TTF-1, synaptophysin and negative for CD45. Additionally, the expanded CTCs demonstrated marked heterogeneity in the expression of E-cadherin and N-cadherin. In a preliminary case series, the drug sensitivity of patient-derived CTC to cisplatin and etoposide was studied to see the correlation with the corresponding therapeutic outcome. In conclusion, our study demonstrates that it is possible to efficiently expand CTCs from SCLC within a clinically relevant time frame, the biomarker information generated from enriched CTCs can assist the selection of effective drugs and improve disease outcome.

Background Radiotherapy is an indispensable treatment modality in head and neck cancer (HNC), while radioresistance is the major cause of treatment failure. The aim of this study is to identify a prognostic molecular signature associated with radio-resistance in HNC for further clinical applications. Methods Affymetrix cDNA microarrays were used to globally survey different transcriptomes between HNC cell lines and isogenic radioresistant sublines. The KEGG and Partek bioinformatic analytical methods were used to assess functional pathways associated with radioresistance. The SurvExpress web tool was applied to study the clinical association between gene expression profiles and patient survival using The Cancer Genome Atlas (TCGA)-head and neck squamous cell carcinoma (HNSCC) dataset (n = 283). The Kaplan-Meier survival analyses were further validated after retrieving clinical data from the TCGA-HNSCC dataset (n = 502) via the Genomic Data Commons (GDC)-Data-Portal of National Cancer Institute. A panel maker molecule was generated to assess the efficacy of prognostic prediction for radiotherapy in HNC patients. Results In total, the expression of 255 molecules was found to be significantly altered in the radioresistant cell sublines, with 155 molecules up-regulated 100 down-regulated. Four core functional pathways were identified to enrich the up-regulated genes and were significantly associated with a worse prognosis in HNC patients, as the modulation of cellular focal adhesion, the PI3K-Akt signaling pathway, the HIF-1 signaling pathway, and the regulation of stem cell pluripotency. Total of 16 up-regulated genes in the 4 core pathways were defined, and 11 over-expressed molecules showed correlated with poor survival (TCGA-HNSCC dataset, n = 283). Among these, 4 molecules were independently validated as key molecules associated with poor survival in HNC patients receiving radiotherapy (TCGA-HNSCC dataset, n = 502), as IGF1R (p = 0.0454, HR = 1.43), LAMC2 (p = 0.0235, HR = 1.50), ITGB1 (p = 0.0336, HR = 1.46), and IL-6 (p = 0.0033, HR = 1.68). Furthermore, the combined use of these 4 markers product an excellent result to predict worse radiotherapeutic outcome in HNC (p

The expression of annexin A2 (ANXA2) in nasopharyngeal carcinoma (NPC) cells induces the immunosuppressive response in dendritic cells; however, the oncogenic effect and clinical significance of ANXA2 have not been fully investigated in NPC cells. Immunohistochemical staining for ANXA2 was performed in 61 patients and the association with clinicopathological status was determined. Short hairpin (sh)RNA knockdown of ANXA2 was used to examine cellular effects of ANXA2, by investigating alterations in cell proliferation, migration, invasion, adhesion, tube-formation assay, and chemo- and radiosensitivity assays were performed. RT-qPCR, Western blotting, and immunofluorescence were applied to determine molecular expression levels. Clinical association studies showed that the expression of ANXA2 was significantly correlated with metastasis (p = 0.0326) and poor survival (p = 0.0256). Silencing of ANXA2 suppressed the abilities of cell proliferation, adhesion, migration, invasion, and vascular formation in NPC cell. ANXA2 up-regulated epithelial-mesenchymal transition associated signal proteins. Moreover, ANXA2 reduced sensitivities to irradiation and chemotherapeutic drugs. These results define ANXA2 as a novel prognostic factor for malignant processes, and it can serve as a molecular target of therapeutic interventions for NPC.

Nasopharyngeal carcinoma (NPC) is a head and neck cancer with poor clinical outcomes and insufficient treatments in Southeast Asian populations. Although concurrent chemoradiotherapy has improved recovery rates of patients, poor overall survival and low efficacy are still critical problems. To improve the therapeutic efficacy, we focused on a tumor-associated protein called Annexin A2 (ANXA2). This review summarizes the mechanisms by which ANXA2 promotes cancer progression (e.g., proliferation, migration, the epithelial-mesenchymal transition, invasion, and cancer stem cell formation) and therapeutic resistance (e.g., radiotherapy, chemotherapy, and immunotherapy). These mechanisms gave us a deeper understanding of the molecular aspects of cancer progression, and further provided us with a great opportunity to overcome therapeutic resistance of NPC and other cancers with high ANXA2 expression by developing this prospective ANXA2-targeted therapy.

When items are classified according to whether they have more or less of a characteristic, the scale used is referred to as an ordinal scale. The main characteristic of the ordinal scale is that the categories have a logical or ordered relationship to each other. Thus, the ordinal scale data processing is very common in marketing, satisfaction and attitudinal research. This study proposes a new data mining method, using a rough set-based association rule, to analyze ordinal scale data, which has the ability to handle uncertainty in the data classification/sorting process. The induction of rough-set rules is presented as method of dealing with data uncertainty, while creating predictive if--then rules that generalize data values, for the beverage market in Taiwan. Empirical evaluation reveals that the proposed Rough Set Associational Rule (RSAR), combined with rough set theory, is superior to existing methods of data classification and can more effectively address the problems associated with ordinal scale data, for exploration of a beverage product spectrum.

Segmentation is particularly challenging in current markets. Hence, companies operating on consumer markets face significant implementation complexities. However, successful implementation of market segmentation is reported problematic, despite being extensively researched and widely acknowledged as a powerful concept in practice. The desired outcome, and the knowledge discovery of market segmentation, is to reap the benefits of competitive advantage. This study takes Computers/Communications/Consumer 3C products as an example and uses a two-step data mining approach to the cluster analysis and association rules to analyze customer channels and product segmentation. Moreover, we look at what kinds of products and brands customers of different segments prefer and how these preferences differ in relation to varying channel types. Thus, this study finds some 3C product-buying behavior patterns, including customer purchase preferences and customer purchase demands, in order to generate different 3C segmentation marketing alternatives.

Research highlights? Direct marketing is an effective marketing method. ? Direct marketing could provide exclusive products and services for specific consumers. ? This study analyzes consumer adumbration, lifestyle habits and purchasing behavior using data mining approach. ? This study finds some models including cluster consumer purchase preference and demand. Direct marketing is an effective marketing method. To compare with the expensive media advertisements, direct marketing could provide exclusive products and services for specific consumers. Also, this method could reduce transaction costs. The communication channel is diverse because virtual shop stores and online shopping are springing up. Therefore, this study proposes the application of Internet marketing to the direct selling industry and the cosmetics market in Taiwan. This study implements association rules and cluster analysis as approaches for data mining. By doing so, we analyze consumer adumbration, lifestyle habits and purchasing behavior. Finally, this study finds some models including cluster consumer purchase preference and demand in order to generate different marketing alternatives for decisions. These research results can help attract more direct marketing firms to open up broader markets and earn higher profits for direct selling.

With advances in modern technology, the Internet population has increased year by year globally. For young customers who consider convenience and speed as prerequisites, online shopping has become a new type of consumption. In addition, business-to-customer (B2C) home delivery markets have taken shape gradually, because virtual stores have risen and developed, e.g. mail-order, TV marketing, e-commerce. To integrate the above statements, this study combines online shopping and home delivery, and attempts to use association rules to determine unknown bundling of fresh products and non-fresh products in a hypermarket. Customers are then divided up in clusters by clustering analysis, and the catalog is design based on each of the cluster's consumption preferences. By this method, to increase the catalogue's attraction to customers, hypermarkets are offered an online shopping and home delivery business model for sales services and propositions. With such a model, we can expect to attract more customers open up more broad markets, and earn the higher profits for hypermarkets.

Background This study was undertaken to identify the genes in response to areca nut extract, a potential carcinogen of oral cancer. Methods Two oral cancer sublines chronically treated with areca nut extract were established. Methods such as microarray and immunohistochemistry were used to screen and validate the genes' altered expressions in areca nut extract-sublines or in cancer tissues. Results A total of 35 genes were differentially expressed in both sublines. Several functional pathways were significantly altered. Six genes were confirmed over 2-fold of changes, including Ches1. Functional analyses showed that overexpression of Ches1 suppressed cell growth and arrested cells in the G2/M phase. Consistently, this gene has reduced expression in 52% of oral cancer tissues, which was significantly correlated with the areca nut chewing habit of patients (p = .04). Conclusion We identified 35 candidates and validated 6 genes that may be associated with areca nut-induced oral cancer. Loss of Ches1 may be attributed to areca nut extract–induced oral carcinogenesis. © 2010 Wiley Periodicals, Inc. Head Neck, 2011

In recent years tourism has become one of the fastest growing sectors of the world economy and is widely recognized for its contribution to regional and national economic development. Tourism product design and development have become important activities in many areas/countries as a growing source of foreign and domestic earnings. On the other hand, customer relationship management is a competitive strategy that businesses need in order to stay focused on the needs of their customers and to integrate a customer-oriented approach throughout the organization. Thus, this paper uses the Apriori algorithm as a methodology for association rules and clustering analysis for data mining, which is implemented for mining customer knowledge from the case firm, Phoenix Tours International, in Taiwan. Knowledge extraction from data mining results is illustrated as knowledge patterns, rules, and knowledge maps in order to propose suggestions and solutions to the case firm for new product development and customer relationship management.

Direct marketing is the use of the telephone and non-personal media to communicate product and organizational information to customers, who then can purchase products via mail, telephone, or the Internet. In contrast, catalog marketing is a type of marketing in which an organization provides a catalog from which customers make selections and place orders by mail or telephone. However, most catalogs for retailing firms are presented to customers in the format of paper catalogs without strategic segmentation design and implementation. In this regard, electronic catalog design and marketing could be a method to integrate the Internet and catalog marketing using market segmentation in order to enhance the effectiveness of direct marketing and sales management in retailing. This paper uses data mining based on association rules from relational database design and implementation for mining customer knowledge. As result, marketing knowledge patterns and rules are extracted for the electronic catalog marketing and sales management of a retailing mall in Taiwan.

The traditional association rule that should be fixed in order to avoid the following: only trivial rules are retained and interesting rules are not discarded. In fact, the situations that use the relative comparison to express are more complete than those that use the absolute comparison. Through relative comparison, we proposes a new approach for mining association rule, which has the ability to handle uncertainty in the classing process, so that we can reduce information loss and enhance the result of data mining. In this paper, the new approach can be applied for finding association rules, which have the ability to handle uncertainty in the classing process, is suitable for interval data types, and help the decision to try to find the relative association rules within the ranking data.

The previous research in mining association rules pays no attention to finding rules from imprecise data, and the traditional data mining cannot solve the multi-policy-making problem. Furthermore, in this research, we incorporate association rules with rough sets and promote a new point of view in applications. The new approach can be applied for finding association rules, which has the ability to handle uncertainty combined with rough set theory. In the research, first, we provide new algorithms modified from Apriori algorithm and then give an illustrative example. Finally, give some suggestion based on knowledge management as a reference for future research.

The Internet has emerged as the primary database, and technological platform for electronic business (EB), including the emergence of online retail concerns. Knowledge collection, verification, distribution, storage, and re-use are all essential elements in retail. They are required for decision-making or problem solving by expert consultants, as well as for the accumulation of customers and market knowledge for use by managers in their attempts to increase sales. Previous data mining algorithms usually assumed that input data was precise and clean, this assumes would be eliminated if the best rule for each particular situation. The Algorithm we used in this study however, proved to function even when the input data was vague and unclean. We provided an assessment model of brand trust as an example, to show that the algorithm was able to provide decision makers additional reliable information, in the hope of building a rough set theoretical model and base of resources that would better suit user demand.

The traditional association rule which should be fixed in order to avoid both that only trivial rules are retained and also that interesting rules are not discarded. In fact, the situations which use the relative comparison to express are more complete than to use the absolute comparison. Through relative comparison we proposes a new approach for mining association rule, which has the ability to handle the uncertainty in the classing process, so that we can reduce information loss and enhance the result of data mining. In this paper, the new approach can be applied in find association rules, which has the ability to handle the uncertainty in the classing process and suitable for all data types.

Head and neck cancer (HNC) is one of the 10 most frequent cancers worldwide, with an estimated over 500,000 new cases being diagnosed annually. The overall 5-year survival rate in patients with HNC is one of the lowest among common malignant neoplasms and has not significantly changed during the last two decades. Oral cavity squamous cell carcinoma (OSCC) shares part of HNC and has been reported to be increasing in the betel quid chewing area in recent years. During 2006, OSCC has become the sixth most common type of cancer in Taiwan, and it is also the fourth most common type of cancer among men. It follows that this type of cancer wreaks a high social and personal cost. Environmental carcinogens such as betel quid chewing, tobacco smoking and alcohol drinking have been identified as major risk factors for head and neck cancer. There is growing interest in understanding the relationship between genetic susceptibility and the prevalent environmental carcinogens for HNC prevention. Within this review, we discuss the molecular and cellular aspects of HNC carcinogenesis in Taiwan, an endemic betel quid chewing area. Knowledge of molecular carcinogenesis of HNC may provide critical clues for diagnosis, prognosis, individualization of therapy and molecular therapeutics.

Background Oral cavity cancers (ORC) are the most common cancers, and standard treatment is radical surgery with postoperative radiotherapy. However, locoregional failure remains a major problem, indicating radioresistance an important issue. Our previous work has shown that GP96 contributed to radioresistance in nasopharyngeal and oral cancer cell lines. In this study, we determined clinical significance of GP96 in ORC by evaluation of GP96 expression and its association with disease prognosis in patients receiving radiotherapy Methods Total of 79 ORC patients (77 males, median age: 48 years old) receiving radical surgery and postoperative radiotherapy between Oct 1999 and Dec 2004 were enrolled. Patients in pathological stages II, III and IV were 16.5%, 16.5% and 67%, respectively. For each patient, a pair of carcinoma tissue and grossly adjacent normal mucosa was obtained. GP96-expression was examined by western blot analysis, and the association with clinicopathological status was determined. Results Three-year locoregional control (LRC), distant metastasis-free survival (DMFS), disease-specific survival (DSS) and overall survival (OS) rates were 69%, 79%, 63% and 57%, respectively. We found that 55 patients (70%) displayed GP96-overexpression in the tumor tissue, which correlated with a higher pN stage (p = 0.020) and tumor depth (> 10 mm) (p = 0.045). Nodal extracapsular spreading (ECS) and GP96-overexpression predicted adverse LRC (p = 0.049 and p = 0.008). When stratified by nodal ECS, the adverse impact of GP96 remained significant in three-year LRC (p = 0.004). In multivariate analysis, GP96-overexpression was also an independent predictor of LRC, DSS and OS (p = 0.018, p = 0.011 and p = 0.012). Conclusion GP96 may play roles in radioresistance which attributes to tumor invasiveness in oral cancer patients receiving radiotherapy. GP96 may serve as a novel prognostic marker of radiotherapy. However, further independent studies are required to validate our findings in a larger series.