Characterization of the hotel sample.
\r\n\tThe discovery of Nylon by Wallace Hume Carothers, a Harvard-educated world-renowned organic chemist born in Burlington, IA in 1896, successfully crowned the attempts developed by E.I du Pont de Nemours & Company to investigate the structure of high molecular weight polymers and to synthesize the first synthetic polymeric fibre.
\r\n\tWhen it hit the market, it was in the form of stockings and all the women in the US wanted to get their hands on a pair. Despite the successful launch of Nylon on the synthetic fibre market and the high expectations created by its extraordinary features, the unexpected war events in 1941 diverted the production of the new synthetic fibre almost exclusively on military applications. Parachutes, ropes, bootlaces, fuel tanks, mosquito nets and hammocks absorbed the production of Nylon, which helped to determine the WWII events. When the war ended and production returned to pre-war levels, consumers rushed to the department stores in search of stockings, accessories and high-fashion garments.
\r\n\tEven if the world of high fashion now seems to more appreciate the use of natural fibres, Nylon is one of the most widely used polymers for the production of technical fibres and fabrics, automotive and micromechanical components. The global nylon 6 & 66 market is expected to reach USD 41.13 billion by 2025, by the following growth at 6.1% CAGR owing to the Increasing focus on fuel-efficient and less polluting vehicles.
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\r\n\tThe amazing success story of Nylon still continues. While its wide availability inspired the development of innovative applications, such as the additive manufacturing, on the other hand, proper disposal after use of high amounts of Nylon resin energised the development of efficient recycling methodology, including chemical recycling. Moreover, the production of Nylon precursors from biomass has become desirable due to the depletion of fossil hydrocarbons and to reduce greenhouse gas (GHG) emissions. This unique combination of technical and socio-economic driving forces is one that aims to further promote the development of Nylon as one of the most suitable ""best polymers"" with a low ecological footprint.
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\r\n\tThe aim of this publication is to unveil the relationships between the chemical structure and the outstanding properties of the broad family of polyamides and to describe the most recent use of Nylon in fostering new applications and promoting a culture aware of environmental sustainability.
Gastric adenocarcinoma (GC) is the second most common cause of cancer-related mortality in the world, with developing countries being the most affected regions [1, 2]. GC is a complex disease influenced by different environmental and genetic factors. Among them, Helicobacter pylori (H. pylori) is the main etiological agent of gastrointestinal infections in children and adults and the prevalence of infection varies considerably across different geographical regions [3]. Natural acquisition of H. pylori infection occurs, for the most part, in childhood [4]. Infection with Helicobacter pylori (H. pylori) promotes chronic inflammation and sequential histological changes of chronic active gastritis, atrophic gastritis, intestinal metaplasia, dysplasia and ultimately invasive carcinoma [2]. Symptomatic diseases occur in approximately 10% of infected individuals, and in these cases, the risk of gastric adenocarcinoma is higher in persons carrying certain strain types as, for example, those that contain cagA or vacA alleles [1].
\nGastric cancer accounts for around 10% of all new cancers (one million per year), and it is the second leading cause of cancer death globally (700,000 deaths per year). The prognosis of CG is very poor, with a survival rate below 30% at 5 years post diagnosis [1, 2]. It is usually asymptomatic or causes nonspecific symptoms at early stages. When symptoms appear, the cancer has usually reached an advanced stage and there is presence of metastasis, being this dissemination a main cause of the severe prognosis. GC-associated high mortality is the result of its silent nature and the extremely high heterogeneity exhibited between individuals and also within gastric tumors. This heterogeneity involves, at the molecular level, a broad variety of gene mutations, amplifications and/or expression alterations, diverse DNA methylation profiles and differences in the activation or inactivation of particular signaling pathways. Thus, in the last years there has been substantial progress in the elucidation of the genomic landscape of GC due to advances in high-throughput technologies and the effort of international consortiums. Consequently, gastric cancer has been recently reclassified and stratified into several distinct subtypes based on molecular and genetic/epigenetic alterations [5, 6]. In particular, GCs have been classified according to defined genetic signatures, the status of TP53 and the presence of microsatellite instability [5, 6]. Importantly, the heterogeneity in GC involves critical consequences in terms of differential response to therapy, resistance and recurrence [6]. Nevertheless, current therapeutic strategies in GC are not adapted to GC heterogeneity and depend on the stage of the tumor. Clinically, first-line treatment consists of surgical resection (except in cases with advanced metastasis), followed by chemotherapy with cytostatic agents such as cisplatin, 5-fluorouracil (5-FU), taxanes or irinotecan, or in combinations as ECF (epirubicin, cisplatin and 5-FU) and 5-FU plus docetaxel or cisplatin (or irinotecan) [1, 7]. These treatments have been internationally and generally accepted and used since last century. In the case of metastatic dissemination, patients whose tumors exhibit high levels of HER2 receptor expression also receive Trastuzumab, a monoclonal antibody against HER2. Initially, patients respond to chemotherapy, but cancer cells eventually become resistant, facilitating the occurrence of relapses. Even with the increase in survival facilitated by the incorporation of chemotherapy, the median overall survival of patients with CG remains low, being one of the survivals associated with cancer lower.
\nIt has been noticed that the incidence of GC has declined over time mostly in developed countries, due to improving living standards. However, and despite increasing knowledge and improvements in the standard of care, therapy resistance and metastasis remain the main causes of treatment failure and death in GC patients and GC as a disease remains a serious and significant social concern. Consequently, identifying the major GC drivers and the molecular and cellular mechanisms responsible for the GC heterogeneity and maintenance is crucial to understand the pathobiology of GC and establish optimal therapies that able to improve the prognosis of patients.
\nSeveral types of solid cancers, including gastric cancers, contain phenotypically and functionally heterogeneous cancer cells [8]. These cancers present a small subpopulation of cells that display characteristics similar to normal stem cells, including unlimited self-renewal, proliferation and multi-lineage differentiation. These cells are called cancer stem cells (CSCs), which are supposed to maintain long-term tumor growth, recurrence and chemotherapy resistance. The origin of gastric CSCs is not completely clear, but it has been observed that this subpopulation of cells can derive from the differentiated gastric epithelial cells, local progenitor cells in the gastric mucosa and bone marrow-derived cells (BMDCs) [9]. In line with this idea, chronic infection of C57BL/6 mice with Helicobacter felis results in chronic inflammation and injury in gastric mucosa, which leads to the loss of resident gastric stem cells, followed by hyperplasia, metaplasia, dysplasia and, ultimately, gastric cancer [10, 11]. H. pylori can attach and invade Lgr5+ gastric stem cells and this residency results in more susceptibility to DNA damage and cancer initiation [12, 13]. This suggests that H. pylori infection directly affects epithelial stem cells in the stomach and plays an important role in transforming resident stem cells into tumor cells. In addition, H. pylori cagA virulence factor unveils CSC-like properties by induction of EMT-like changes in gastric epithelial cancer cells [14]. Increasing studies support the existence of these cancer cells exhibiting stem cell characteristics and involved in GC metastasis [14]. Among the underlying mechanisms of chemoresistance, CG cells resistant to 5-Fluoroacyl (5-FU) or cisplatin therapy have been identified as exhibiting high expression of stem cell markers such as BMI1, CD44, CD133 or SOX9. In addition, the inhibition of these regulators reverses the chemoresistance. This resistance is due in part to the acquisition or presence of quiescence and self-renewal characteristics by the small percentage of gCSCs. It is well known that conventional chemo and radiotherapy therapies have maximum efficacy in proliferative cells and when target events are present in all cancer cells. However, they do not affect the quiescent cells and do not take into account inter and intratumoral heterogeneity at the cellular and molecular level. Thus, identifying the major regulators of gastric CSCs is a prominent need in order to understand GC pathobiology and identify novel therapeutic targets. In this sense, in the last years, the identification of several stem cell-related genes or transcription factors has provided relevant information of the impact of gCSCs in GC initiation and progression, and how H. pylori or chronic inflammation affects gastric stem cells. This chapter summarizes the impact of some of the most relevant genes in gastric CSCs and gastric cancer pathobiology, including LGR5, CD133, CD44, SOX2 and SOX9.
\nThe human leucine-rich repeat-containing G protein-coupled receptor 5 (LGR5) is a member of the G protein-coupled transmembrane receptor (GPCR) superfamily. LGR5 is a receptor for R-spondins that belong to the WNT signalling complex at the membrane level [15] and is also a target gene of this pathway [16]. LGR5 is overexpressed in a variety of human cancers, including tumors of the digestive tract such as colorectal [17] or gastric cancer [18–20], wherein it has been postulated as a CSC marker. LGR5 is an established stem cell marker of the intestine, and several studies on mice and humans have shown that LGR5-positive stem cells are the cells-of-origin of intestinal and colorectal cancer [21–27]. In the stomach, there are also increasing evidence postulating LGR5 as a stem cell and CSC marker. Thereby, LGR5 expression in gastric mucosa is almost restricted to a subset of cells located at the base of the pyloric glands, distribution that fits well with the multiple sites of the gastric cancer in humans [28]. Through in vivo lineage tracing experiments, these authors found that LGR5-positive cells were self-renewing and multipotent and were responsible for the renewal of the gastric epithelium. Interestingly, they observed that the transformation of this population of stem cells could drive gastric tumorigenesis in vivo [28], fact that has been strongly demonstrated more recently by Li and collaborators [29]. Consistently with the observation in mice, in human gastric tissue, LGR5 expression has also been found in the bottom of gastric glands [30]. Supporting the putative role of LGR5 as a gastric CSC regulator in humans, independent studies have reported LGR5 overexpression in human gastric cancer samples respect to normal gastric mucosa in a progressively increasing manner from well-differentiated to poorly differentiated gastric carcinomas [20, 31]. Furthermore, LGR5 expression has been strongly linked to a high degree of tumor infiltration, high TNM stage, recurrence and dismal prognosis of gastric cancer patients [18–20, 31]. More recently, Wang and collaborators have shown that sphere cells derived from a gastric cancer cell line presented increased expression of some canonical stem regulators, being LGR5 particularly elevated [32]. They also showed that ectopic LGR5 overexpression potentiated the sphere cell growth and cell migration capabilities of gastric cancer cells and also their tolerance to oxaliplatin, associating LGR5 expression with the characteristic features of CSCs [32]. These findings are in concordance with previous observations showing the impairment of the invasiveness and the reduction in the expression of metalloproteinase 2 (MMP2) and β-catenin in gastric cancer cells in response to LGR5 silencing in vitro; and revealing a positive correlation between the expression of LGR5 and MMP2 in gastric cancer tissue samples [20]. Regarding the implications of the carcinogenic agent H. pylori in the LGR5-positive cells in the stomach, it has been found that this population of cells is expanded in gastric cancer tissues affected by the bacteria, indicating that LGR5 likely represents a marker of stem cells susceptible of oncogenic transformation driven by H. pylori [13, 33].
\nCD133 (also Prominin 1) is a pentaspan transmembrane glycoprotein present in embryonic epithelial structures, thought to function as an organizer of plasma membrane topology, and regulating the maintenance of the appropriate lipid composition within the plasma membrane [34]. CD133 has been presented as a marker of cancer stem cells in colon, pancreas, brain or lung cancer [35], yet its role in gastric CSCs is controversial. Several findings related to different aspects of gastric CSCs have been published in support of its role as a gastric CSC marker and regulator. In gastric cancer cell lines, CD133 silencing abrogates sphere formation capacity [36] and, consistently, CD133 has been found overexpressed in gastric sphere cultures [37, 38]. Noteworthy, a large number of publications show increased CD133 expression in human gastric cancer tissue respect to non-neoplastic gastric mucosa and highlight the prognostic significance of CD133, associating its overexpression with a big plethora of adverse clinic-pathological features, such as elevated cellular proliferation rates, high T stage, venous invasion, lymph node and distant metastasis, chemoresistance, recurrence, poor 5-year disease-free and overall survival and so on [37, 39–42]. According to this, studies performed in gastric cancer cell lines demonstrate that CD133-positive gastric cancer cells present a CSC phenotype, since they are more tumorigenic, more chemoresistant and exhibit higher migration or invasion capacities than CD133-negative cells [37, 38, 43]. However, some controversial findings have been published indicating that CD133 expression is not a sine qua non condition for gastric cancer cells to exhibit properties of CSCs. Thus, Takaishi et al. isolated different subpopulations of cells from gastric cancer cell lines according to the expression of CD133, CD44, CD26 and other cell surface markers and showed that CD133-positive cells did not exhibit characteristics of CSCs [44]. Similar results have been obtained in other investigations using human gastric cancer specimens as source of cells, in which CD133-positive cells were not able to reproduce tumors in immunodeficient mouse models [45, 46].
\nCD44 is a transmembrane glycoprotein expressed on leukocytes, endothelial cells, hepatocytes or gastric epithelial cells, which acts as a receptor for hyaluronic acid (HA) [47] and can also interact with other ligands, such as osteopontin, collagens and MMPs. CD44 is a fetal and adult hematopoietic stem cell regulator that is involved in cell-cell interactions, cell adhesion and migration and participates in a wide variety of cellular functions, including hematopoiesis and lymphocyte activation, recirculation and homing [48]. CD44 gene contains 20 exons. Ten of these exons (exons l–5 and 16–20) are expressed together on many cell types and the product is referred to as the “standard” form of CD44. Additionally, complex alternative splicing of the transcripts affecting exons from 6 to 15 (variant exons) results in many functionally distinct isoforms or variants (CD44v) [49]. The role of CD44 as a CSC marker has been broadly studied in myeloid leukemia and also in several solid tumors such as lung, brain, liver, head and neck or gastric cancer [50]. In gastric cancer, the first temptative characterization of CSCs in terms of markers was performed by Takaishi and collaborators, who found that CD44+ cells isolated from different gastric cancer cell lines presented sphere formation ability in vitro and tumorigenic potential when inoculated into stomach and skin of immunodeficient mice, abilities that were abrogated by CD44 silencing. Moreover, these CD44+ gastric cancer cells showed the stem cell characteristics of self-renewal and the ability to give rise to differentiated progeny [44]. In concordance, other authors have documented CD44 enrichment in spheres derived from gastric cancer cell lines [51] or have identified that CD44-positive cells derived from gastric cancer cell lines are resistant to 5-fluorouracil and cisplatin chemotherapy and also exhibit significantly more migration, invasion and anchorage-independent growth capabilities [52]. Regarding gastric cancer clinical samples, CD44 is expressed in 80% of gastric tumor resected specimens [40] and its high expression has been associated with tumor size, lymphatic vessel and intravenous invasion, moderate grade of differentiation and low response to chemotherapy [52–54]. Furthermore, the presence of CD44+ cancer cells at the invasive front of gastric tumors entails poor survival and constitutes a prognostic factor for this malignancy [55]. In relation to this aspect, Watanabe and collaborators have found that in gastric cancer patients, the frequency of circulating CD44-positive tumor cells correlates with disease stage, depth of tumors and venous invasion [56]. Moreover, it has been suggested that the emergence of gastric CSCs induced by H. pylori infection of gastric mucosa may rely on CD44 upregulation [57]. Nevertheless, in contraposition to these evidences, some works have not found CSC characteristics in the subpopulations of CD44-positive cells isolated from gastric tumors [45, 58]. Besides, it is being sustained the notion that some CD44 variants are more relevant for gastric CSCs than standard CD44. An example of it is the work of Lau and collaborators, who show that CD44v8-10 is the predominant CD44 variant expressed in gastric cancer cells, whose expression levels, unlike those of standard CD44, are increased in gastric tumors respect to adjacent normal tissue. The authors also showed that ectopic expression of CD44v8-10, but not standard CD44, in gastric cancer cells potentiates their ability to initiate tumors in mice at limiting cell concentrations and that total CD44 silencing impairs tumor-initiating potential of cells, which could be rescued by restoration of CD44v8-10, but not standard CD44, expression [46].
\nCD24 encodes a cell surface sialoglycoprotein that is physiologically expressed in developing or regenerating tissues and regulates processes such as lymphocyte development [59] or neurogenesis [60]. As other stem cell genes, CD24 is expressed in hematologic malignancies and several solid tumors including gastric cancer. Suggesting a role for CD24 in gastric CSCs, some studies by using gastric cancer cell lines have shown that derived spheres are enriched in the expression of CD24 (and CD44) [51] and also that CD24 modulates positively cell migration, while its inhibition entails apoptosis [61]. However, Takaishi et al. were unable to find properties of CSCs in a CD24-positive population in terms of sphere forming capacity and tumorigenicity in mice models [44]. With regard to patients with gastric cancer, CD24 expression progressively increases in samples of normal gastric mucosa, non-atrophic chronic gastritis, chronic atrophic gastritis, intestinal metaplasia, dysplasia and gastric cancer [61]. Moreover, CD24 expression has been associated with adverse clinicopathological and prognostic aspects such as depth of tumors, lymph node status, TNM stage and reduced overall survival [62], fact that underlines its relevance in the disease.
\nSOX factors are a family of transcription factors that are emerging as potent regulators of stem cell maintenance and cell fate decisions in multiple organ systems including the gastrointestinal tract [63]. There are at least 20 members divided into eight groups (from A to H), based on their HMG sequence identity in humans. Members within a group preserve higher than 80% identity in their HMG-domain and share other well-conserved regions. In addition, they share biochemical properties, have overlapping expression patterns and perform synergistic or redundant functions [63]. SOX proteins play critical roles during the development of several cell types and tissues in the embryo. They are also essential for stem cell types in the adult through the regulation of the cell fate determination, differentiation and proliferation [63]. SOX members fulfill their role by activating or repressing transcription and their action on target genes is context dependent, relying on other transcription factors with which they may directly interact for specificity. Dysfunction of SOX factors has been implicated in several human diseases. Such diseases are consistent with SOX function and expression pattern during embryonic development. A growing number of evidences are demonstrating that the expression and function of SOX factors are altered in a variety of cancers, and their roles in these malignancies are related to their stemness feature [64].
\nSOX2 belongs to the SOXB1 subgroup along with the closely related SOX1 and SOX3. SOX2 is required for establishing embryonic stem cells and the maintenance of the early embryo [65]. It is also one of the factors necessary for reprogramming terminally differentiated cells into induced pluripotent stem cells [66]. Furthermore, SOX2 belongs to the core transcriptionally circuitry found on the regulatory regions of many genes with embryonic stem cell-specific expression [67]. This evidence demonstrates that SOX2 is a key factor in the control of embryonic stem cells fate and activity. SOX2 has additional functions during development, thus emerging as a critical regulator of stem cell maintenance and cell fate decisions. Furthermore, SOX2 also plays a relevant role during adulthood controlling tissue homeostasis and regeneration. Its expression is elevated in different populations of stem cells [68–71], and its high levels can be used to identify quiescent stem cells and distinguish them from transient amplifying progenitors [72, 73]. SOX2 is a regulator of gastric stem cells highly relevant for gastric patterning during development [74] and involved in the physiological renewal of the gastric epithelium in the adulthood [71, 75]. SOX2 displays several roles in cancer as an oncogenic driver, prognostic factor or a marker and regulator of CSCs [76–80]. In GC, its action is controversial. Several authors observed that SOX2 is frequently downregulated in gastric cancer [81–86]. Furthermore, low SOX2 expression is associated with shorter survival time [82] and also with worse prognosis [84]. In contrast, higher SOX2 levels are found among patients who have better prognosis [84]. In a large set of patients, Wang and coworkers demonstrated that SOX2 expression is progressively reduced during gastric carcinogenesis, from normal into invasive cancers including a series of premalignant states, supporting the role of SOX2 decrease as a robust predictor of disease outcome [85]. Similarly, SOX2 downregulation is linked with diffuse type of cancer with SOX2 expression becoming a good biomarker to discriminate between tumor (negative) and non-tumor (positive expression) and also high/low grades of tumor malignancy [86]. The regulation of SOX2 expression in GC has been mostly associated to epigenetic changes. Thus, aberrant DNA methylation has been shown as a key mechanism underlying SOX2 downregulation in a set of primary gastric carcinoma samples [82]. Besides promoter methylation, miR-126 overexpression also decreases SOX2 levels and therefore acts as a tumor suppressor [83]. Recently, it has been shown that SOX2 has an important role in gastric differentiation [87]. It is known that during gastric carcinogenesis, the homeobox transcription factor CDX2 is critical for intestinal differentiation driving the onset of intestinal metaplasia (IM) [88, 89]. Thereafter, Camilo and coworkers showed that SOX2 is associated with gastric differentiation in incomplete IM and is lost in the progression to dysplasia, whereas CDX2 is acquired de novo in IM and maintained in dysplasia [87]. Taken it into account, the authors hypothesized that balance between gastric and intestinal differentiation programs might interfere on the gastric carcinogenesis progression [87]. Since SOX2 and CDX2 expression were found in about half of the cases, the interaction of both transcription factors in gastric carcinogenesis remains to be investigated. Functional characterization performed in gastric epithelial cell lines showed that SOX2 ectopic activation inhibits cell proliferation through G1 cell-cycle arrest and induces apoptosis by decreasing cyclin D1 and phosphorylated Rb and increasing p27Kip1 protein levels [82]. Overall, the authors observed that SOX2 performs a critical part in gastric carcinogenesis, operating as a tumor suppressor. Similarly, Wang and coworkers verified that enforced SOX2 expression inhibited proliferation, increased apoptosis and reduced invasion and motility, both in vitro and in vivo [85]. Mechanistically, SOX2 directly transactivates PTEN. Therefore, this SOX2-dependent PTEN upregulation may directly orchestrate downstream phospho-Akt dephosphorylation, affecting diverse cellular phenotypes such as survival, growth, proliferation and migration [85]. These studies show that SOX2 plays important roles in gastric epithelial cells growth inhibition through cell-cycle arrest and apoptosis [90]. Regarding its relationship with H. pylori, SOX2 expression is decreased by the bacteria, and this inhibition leads to an upregulation of CDX2 expression [75, 91, 92]. Additionally, in vitro and in a mice model infected with Helicobacter spp. demonstrated that CDX2 and SOX2 are downstream targets of the BMP (bone morphogenetic protein) pathway in gastric carcinogenesis. The authors showed that H. pylori upregulates BMP pathway, through an increase in BMP2, SMAD4 and pSMAD1/5/8 expression. Thus, SOX2 expression was downregulated by H. pylori and the BMP pathway [93]. From a mechanistic perspective, it was postulated that the activation of an intestinal differentiation program may occur concomitantly with the silencing of a gastric differentiation, induced or controlled by SOX2 [93]. Another recent study identified that the bacteria might trigger its pro-carcinogenic activity through a blockage of SOX2 [85]. However, other authors verified that overexpression of SOX2 is associated with tumor invasion, lymph node metastasis and chemoresistance [94–97]. Tian and coworkers were able to show that SOX2 enhances the tumorigenicity and chemoresistance of cancer stem-like cells derived from gastric cancer, suggesting an oncogenic effect of SOX2 in the stomach [94]. In addition, it has been demonstrated that SOX2 overexpression was significantly correlated with lymph node metastasis and the stage of tumor invasion in gastric cancer indicating that SOX2 might be a predictive prognostic factor [95]. Hutz and coworkers proved that high levels of SOX2 are involved in gastric carcinogenesis by regulating the expression of genes associated with proliferation, apoptosis and cell cycle regulation, in vitro and in vivo [96]. Functionally, the SOX2 suppression induced a decrease in cell proliferation, which coincided with an increase of apoptosis in AZ-521 cells. Similarly, blocking of SOX2 in a xenograft mouse model resulted in reduced tumor growth [96]. Moreover, the expression of SOX2 in human gastric tumor samples was observed at high proliferation rate sites [96]. Likewise, SOX2 overexpression in gastric cancer has been recently observed in other study, where the surge in the expression is attributed to SOX2 locus copy number variation, being related as well with the presence of regional lymph node metastases [98].
\nSOX9 is overexpressed in a variety of human cancers, being its high levels correlated with malignant character and progression in prostate, lung, breast and brain tumors [80, 99, 100]. SOX9 expression is also elevated in tumors of the digestive system such as esophageal, colorectal and pancreatic cancers [101, 102]. In esophageal and pancreatic tumors, SOX9 stimulate self-renewal properties [102, 103]. However, in colorectal cancer, there are contradictory results between functional studies and clinical samples, suggesting a context-dependent activity of SOX9 [100, 104]. Remarkably, several studies have reported clinical implications of SOX9 in GC. Thereby, in GC patients, high tumoral SOX9 expression has been observed and associated with advanced TNM stages and lower overall patient survival [105]. Interestingly, in clinical samples, high levels of SOX9 correlate with elevated expression of the carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) [106], which facilitates GC metastasis, and are positively associated with lymph nodes metastasis and advanced TNM stage [107]. In samples from patients, there is also an inverse relation between SOX9 and the tumor suppressor gastrokine 1 (GKN1), relationship also observed in GC cell lines, wherein GKN1 negatively regulates SOX9 expression [106, 108]. Furthermore, elevated SOX9 expression in gastric tumors is associated with the activation of the WNT canonical oncogenic pathway, with whom it establishes a feedback regulatory loop [105].
\nNoteworthy, SOX9 is a critical executor of the carcinogenic action of H. pylori. According to this notion, the bacterium induces SOX9 expression in pre-tumorigenic gastric mouse cells [109] and also in GC cells [105], being the induction more pronounced in response to specimens of H. pylori containing the pathogenically significant CagA virulence factor. Notably, SOX9 is required for bacteria-induced GC cell proliferation, induction of β-catenin and acquisition of stem cell-like properties. Mechanistically, it has been found that TNFα and IL-1β cytokines, involved in the inflammatory response to H. pylori, induce the expression of SOX9 in mouse models and GC cells [105, 109], being probably the action of TNFα in human GC cells stronger and more extensive. In fact, TNFα high levels correlated with SOX9 upregulation in H. pylori-positive GC samples, and there was a positive association between them in two independent large cohorts of GC samples [TCGA and ACRG] [105]. Overall, these results identified a novel association between SOX9 and IL1-β and TNFα cytokines, which links H. pylori infection with SOX9 and GC outcome in patients, evidence supported by other studies [110–114]. SOX9 represents a key driver of GC and given the importance of its strong clinical implications, elucidating the molecular mechanism of its action in GC has constituted an important challenge to identify novel and suitable therapeutic targets. With respect to that, it is known that SOX9 establishes a feedback regulatory loop with WNT/β-catenin signaling pathway. Consistently, SOX9 abrogation in GC cells diminishes CYCLIN D1 and c-MYC expression, and there is a positive correlation between these genes and SOX9 in patient samples [105]. Functionally, SOX9 silencing in GC cells promotes apoptosis and senescence through BMI1 decline and the consequent upregulation of p21CIP [105]. SOX9 silencing also supposes detrimental effects on the subpopulation of gCSCs, reflected by a reduction in tumorsphere self-renewal and decreased tumor initiating capability [105]. Paralleling these effects, and likely due to its functions in gCSCs, SOX9 mediates cisplatin chemoresistance [105, 114], fact that might explain the reduced disease-free survival of patients presenting tumors with high SOX9 expression levels [105]. Additionally, there are other SOX members associated to GC. Thus, SOX4 has been shown to display pro-oncogenic activities and become upregulated with gastric cancer progression, in the population of gCSCs and in response to H. pylori infection [115–117]. Finally, SOX18 mRNA levels are increased in gastric cancer tissues compared to normal tissue, and the frequencies of both lymphovascular invasion and lymph node metastases are higher in SOX18 positive than in the negative group. Furthermore, both the 5-year survival and the recurrence-free survival were shorter for SOX18-positive cancers suggesting that SOX18 expression might be a prognostic tumor marker and a potential therapeutic target in gastric cancer [118].
\nConsumers increasingly use online means to share their experiences and perceptions about the quality of services they use. Every day overwhelming volumes of information are produced and published online, and these seem to exert a critical influence on service choices and purchase decisions. This context is very much facilitated by the dissemination of technologies that encourage the production and sharing of user crated content. Likewise, there is a growing familiarity of customers with Internet technologies that is fueling this trend. Service providers, by their turn are keeping the pace by implementing and adhering to online tools that offer efficient ways for users to make their ideas available to vast audiences in a fast manner [1]. The importance of such form of communication, known as electronic word-of-mouth (eWOM) or word-of-mouse, has been extensively acknowledged in the literature, often being referred as a more effective means to influence customers’ consumption decisions than other tools, such as personal sales or advertising, because it can be perceived by costumers as a rather reliable source of information. Whereas customer reviews are now a common feature in many company websites, and platforms, research is still necessary to gain knowledge about how to effectively use eWOM data as a valued adding tool to inform customer decision making, as well as to guide managerial actions towards service improvement and innovation. This study proposes a contribution in this direction.
The study describes the development of a methodology to support the analysis of eWOM, in order to facilitate the systematic analysis and visualization of insights from online reviews concerning service quality. The proposed methodology is useful to both academics and managers as it proposes a concise display of the data analysis results, allowing for a quick identification and debate about priorities and concerns for quality management, while building on a frame of reference for quality attributes that is derived from service management literature. The study was developed in the particular context of the hotel industry in Portugal, as a representative business sector for the volume and reach of online consumer reviews. The development of the proposed data analysis and display method was built on a selected sample of customer reviews extracted from a prevalent online service for hotel bookings. The hotel industry offers an adequate and rich context for the nature of this study for the fact that the travel and tourism industry is known for being a pioneer for the growing trends of promotion and distribution of services over the Internet [2].
The chapter offers an approach for making sense of customer reviews, by identifying relevant service quality dimensions embedded in the voices of hotel customers, while offering a concise tool for the visualization of the results. To this end, the study employed the principles of importance-performance analysis (IPA), a marketing research technique acknowledged for offering a concise graphical representation of results, to develop a framework for identifying salient hotel service attributes from the available and uncategorized information provided by customer reviews. The study offers a timely approach for assisting managers in the task of sense making from growing volumes of user generated information from a key source of information for the identification of priorities for service improvement and innovation.
Following this introduction, this chapter offers in Section 2 an overview of the conceptual background of the study, namely addressing on the topics of service quality and service quality assessment approaches while discussing some of the key challenges in measuring service results. In Section 3 is devoted to describe the application of the importance-performance analysis (IPA) approach to the context of eWOM in hotel services, and to presented and discuss some representative results of the application of this methodology to extract meaning from user generated context. The chapter closes with a presentation of key contributions and conclusions in the last section.
The understanding of service quality and the deployment of robust and replicable methods to conduct its assessment have been in the core of the agendas of service management scholars and practitioners for many years. Despite an early consensus about the relevance of service quality for customer satisfaction, loyalty and company’s profitability [3, 4], the operationalization of methods and tools to measure service quality and inform managerial practice and consumer decision making has generated extensive debate and challenges. Many of the results of service experiences lack tangibility and for this reason many approaches for service quality assessment rely on information from customers’ “perceived” experiences [5, 6].
Many of the prevalent approaches to capture consumers quality perceptions build on the development of survey methods for data collection, consisting of multi-item scales. Such multidimensionality is aligned with the conceptualization of services as experiences that enact perceptions about multiple attributes and dimensions that affect customer value such as service responsiveness, reliability, and even elements such as the characteristics of the tangible elements such as service facilities, equipment, etc., and the performance and empathy of service professionals. In service experiences customers receive a combination of outcomes including direct process results (e.g., availability of required items in a retail store, on-time arrival to a flight destination in transportation services, etc.) along with other results related to the process experience resulting from customers’ contact and involvement in the service process (e.g., store atmosphere in retail services, comfort in a flight, etc.). Service quality is therefore conceptualized as a construct, featuring distinct dimensions that correspond to the diverse benefits that a customer can derive from a service. These dimensions of service quality are present across the prevalent service quality models and mirrored in the generalized generic scales such as SERVQUAL, SERVPERF, along with other sector specific scales where items are adapted to business particularities, such as in retail, health or hospitality and tourism services. Prevalent models account for the recognized dual nature of service quality determinants, i.e. the quality of service outputs as well as the quality of the experience with the delivery processes [4].
Overall service quality models, and the derived methods for its assessment, analysis and interpretation are built on customers’ perceptions about the performance of service delivery, rather than on objective assessments of quality items [7, 8]. Perceived service quality is defined as the customer’s evaluation of the overall excellence of a service and has been persistently distinguished from objective quality measurements, which were typically associated to the quality assessment of manufacturing products. The use of perceived service quality models is motivated by the specific nature of service outputs, which involves both tangible and intangible components and, as such, are often hard to assess and can result into very heterogeneous evaluations across customers.
Despite of the popularity of the [quantitative] multi-attribute type of measurement that has prevailed in the service quality domain along the years, several debates have highlighted the limits of such instruments. Among these are the difficulties of interpreting and using the standardized results of multi-attribute measurements. Data collected in this form offers only limited information about the richness, and the details, that contextualize customer perceptions about a service. More importantly, survey data fails from capture information about contradictions in service experiences as the respondents are forced to aggregate their quality experiences into ratings for a limited number of items. Any comprehensive listing of all quality aspects would result into lengthy questionnaires that would exceed customer’s willingness to answer and therefore hurt the validity of the information collected. A customer of an accommodation service of asked to evaluate the friendliness contact employees is forced to choose a single point on a scale despite the number of contacts and different staff met whose behavior and friendliness might vary considerably.
Overall the standard attribute-based quality and satisfaction surveys are not perfect when it comes to capturing all relevant managerial information, and for this reason other complementary approaches have been advanced, such as focus groups studies, analysis of critical incidents, among others, in order to capture richer consumer insights. In this context, word-of-mouth, i.e. the expressions about the service experiences as expressed in the words of the consumers have always been acknowledged as an important source of information, and a key determinant for consumer choice. Generally, it is referred to as an informal and personal form of communication [9] that has been acknowledged by its influence for customers ‘decisions [10], being source of trusted information [11].
In recent years, the advent of electronic-word of-mouth (eWOM) has created a rich field of data for deepening the understating about consumer experiences. Differently from traditional WOM, the its electronic version eWOM offers the advantage of being preserved, and accessible, over time in a written format that can be revisited and analyzed in detail, with distinct lenses.
The volume and reach of eWOM content have expended enormously, and are increasingly calling for the development of methods and tools that can assist consumers and managers to filter and make sense, in a timely manner of such large and rich amount of information. Consumers are expressing their opinions using multiple sources that include blogs, online reviews, and social networking websites, while interacting virtually to share information about their experiences with all sorts of goods, services, and brands [12]. eWOM has been defined as “any positive or negative statement made by potential, actual or former customers about a product or company, that is made available to a multitude of people and institutions via the internet” ([1], p. 39).
The tourism sector is a prominent example of a setting where eWOM has grown in volume and popularity, notably by means of online reviews that are the concrete examples of electronic versions of traditional WOM and result in a volume of comments from travelers about their experiences, the products, and the services they find along their journeys [13]. eWOM is available for other tourist to read and revisit, as well as for service managers to learn about their experiences. In fact many of the tourism service providers actively encourage their consumers to post reviews on their sites, social media platforms and other sources of reference [14]. The growth in eWOM is motivating increased research attention in several fronts, such as the investigation of the impacts of eWOM on sales, on consumer behavior. In tourism industry the results support that eWOM is considered credible [15], reducing consumers resistance to booking [16] and affects the sales of hotel rooms [17] and the motivations to visit some specific destinations [18]. Despite the growing number of studies that cover, the field is still far from being fully covered, and is still very much concentrated in exploring the behavioral implications of eWOM on travelers [19]. In this study we take a different approach aimed at developing approaches to make sense of the rich information contained in the reviews’ texts with the purpose of advancing in the creation of tools to support data analysis and visualization that can assist managers and consumers in extracting valuable information from eWOM sources.
Importance-performance analysis is a popular approach for interpreting customer satisfaction and for setting up priorities for upgrading service quality proposed by [20]. IPA builds on customers’ assessments concerning the importance and the performance of quality attributes in order to diagnose areas for improvement—typically using data collected by means of questionnaires employing service scales. IPA offers a plot representation for the measurements for importance-performance, declared by customers, consisting of a four quadrants matrix. The IPA matrix plots these values against two axes: a vertical axis—for the values of performance of service attributes; and an horizontal axis—for the values of attribute importance (see Figure 1).
Quad chart illustrating the breakdown of traditional importance-performance analysis approach. Desirable re-allocation of resources would go from the lower right quadrant to the upper left quadrant. Source: Adapted from Martilla and James [20].
Such concise display enables the quick visual identification of what elements demand for managerial improvement actions (i.e. attributes ranked in the quadrant for high importance vs. low performance) as well as others where the providers efforts are potentially misplaced (i.e. attributes ranked in the quadrant for low (customer) importance vs. high (provider) performance).
Subsequent studies have proposed modified approaches building on the principles of the IPA framework, extending its scope of application. For example CIPA, that stands for “Competitive Importance Performance Analysis”, is focused on the gaps of the performance of a given service company and that of its competitors, offering a tool to diagnose which competitive attributes demand for improvement. In this adaptation the horizontal axis represents the differences between a company’s performance towards the other market players.
Other formulations of IPA aim to address criticisms about its assumptions, namely the independence between the importance and performance measures and the linear relationship between the attributes and the performance. The so-called IPA with the three factor theory employs also a matrix representation for the measurements but takes into account the fact that not all service attributes are equally important for customer satisfaction [21, 22, 23]. This approach distinguishes three types of factors: (i) basic factors, i.e. minimum requirements that cause dissatisfaction if not fulfilled while not leading to customer satisfaction if fulfilled; (ii) performance factors, i.e. elements that cause satisfaction or dissatisfaction, depending on their performance level and (iii) excitement factors that can increase customer satisfaction if delivered but do not cause dissatisfaction if not delivered [24]. The modified IPA approach employs this three factor theory [25] and uses estimations of the relative importance of the quality attributes, instead of using customer declared information. The importance-performance lens of analysis therefore offers a versatile methodology for approaching the prioritization of service attributes.
This study builds on prevalent approaches of extending the applications of IPA by developing a modified version of IPA for identifying areas for service improvement building on qualitative data in the context of hotel experiences.
The main purpose of this work is to develop a flexible and concise methodology to make sense for the ever growing online customer reviews that are available for a wide diversity of service business, in an abundant and unstructured manner. Despite the volume and richness of data available, the ability of both customers and providers to summarize and interpret customer generated content is still very limited and often done ad hoc by managers, therefore hurting its utility and value for customer decision and company improvements. Yet recent research results confirm that such sources of information are increasingly accessed by customers to support purchase decisions [26]. To this end, the study focuses on customer online reviews in the context of the hotel industry for several reasons. Tourism and hospitality services are experiential in nature which makes pre-purchase quality assessments rather difficult, leading customers to search for various clues and information to support their choices. In this context the opinions of other customers assume a critical role. In addition this service industry has a pioneering record in the utilization of online means for customer service interactions (e.g. travel reservations), and for the abundance of eWOM behavior.
The study addresses a sample of customer reviews for a selected number of hotels in a medium sized tourist destination city in Portugal available in the online reservation website
Hotel | Star rating | Rooms | Location* | Available services | Average price** |
---|---|---|---|---|---|
Moliceiro | 4 | 49 | 0 | 16 | € 99 |
Aveiro palace | 4 | 49 | 0 | 13 | € 62 |
Melia Ria | 4 | 128 | 10 min | 22 | € 94 |
Américas | 4 | 70 | 5 | 16 | € 79 |
Imperial | 3 | 107 | 0 | 8 | € 63 |
Jardim | 3 | 48 | 0 | 11 | € 56 |
Afonso V | 3 | 78 | 5 | 6 | € 49 |
Veneza | 3 | 49 | 0 | 7 | € 68 |
Aveiro center | 2 | 24 | 0 | 8 | € 58 |
J. Estevão | 2 | 12 | 1 | 6 | € 57 |
Salinas | 2 | 18 | 0 | 7 | € 58 |
Characterization of the hotel sample.
Walking time to the city center (minutes).
Standard double room, average.
The first column contains the hotel name, the second column the official star rating at the time of the study, the third contains the number of rooms and the fourth the estimated walking time to the city center. The fifth and sixth columns present the number of services available at the hotel and the average price per night, respectively.
The chosen hotel reservation Website exhibits written online customer reviews, organized into groups—positive and negative reviews—as well as a rating obtained from customer scoring. In order to guarantee reliability, i.e. that the reviews resort from individual experiences, the Website only allows for reviews from customer who have effectively made a reservation.
The IPA addresses the data from the sample of extracted customer reviews. The first step in the analysis involves the identification of the most frequent terms and expressions about the hotel experience as stated by customers, for which text mining tools were employed, including a preliminary cleaning of symbols and words with no relevant meaning, and the standardization of terms, whenever synonyms are used to refer to a same hotel service element. The terms and expressions with higher frequency were retained for inclusion in the IPA analysis. A second step involves the identification of dimensions of affinity for the service quality attributes present in customers’ statements. This process leads to the identification of three dominant service quality elements, motivating the expression of (positive or negative) customer opinions: room, location and staff. Whereas a more detailed list if attributes can be retained the choice is for the use of a more aggregated level of analysis given the exploratory nature of the study.
The IPA matrix for the 11 hotels is displayed in Figure 2, where the data points for importance-performance for the three salient attributes, room, location and staff are, respectively ●, ▲ and *. In the traditional IPA the horizontal and vertical axis represent the coordinates for the values of importance, and the performance as perceived by the customers, usually resulting from structured questionnaire answers, using ordinal scales (e.g. 1–7), where customers sate their expectations (i.e. interpreted as importance) and service perceptions (i.e. experienced performance). In the current study, and given the qualitative nature of the available data—the reviews—the values for the matrix coordinates are obtained as follows.
Modified IPA graph for the hotel sample in the study.
For each service attribute (room, location and staff) the total frequency (considering all the terms and expressions associated to a given service attribute) is employed as a proxy for the importance of the attribute, therefore assuming, that customers express more opinions for items that are more relevant for their experience. As for performance, the analysis employs the ratio of the number of positive reviews towards the sum of positive and negative comments, for a given service attribute. According to this logic a hotel for which the proportion of positive comments is higher than the negatives corresponds to a positive performance. This proxy measurement for performance therefore varies between 0 (when all comments are negative) and 1 (when all comments are positive). Also, the traditional IPA usually employs a central tendency measure (e.g. mean, median) to split each axis and identify the four quadrants. In the current study the value of the mean is employed to split the plot area.
The interpretation of the IPA graph offers a number of interesting insights. Overall, for each hotel unit, the three service attributes considered in the analysis are closely positioned next to each other. This suggests that when hotel customers are pleased with a hotel, or with the particular performance of one service attribute and they engage in offering positive comments, they tend to be positive about the remaining attributes. Whereas there’s some natural dispersion in the points exhibited in Figure 2 most service attributes, for the diverse hotels, is positioned in the quadrants II and IV pointing towards urgent action and resource underutilization, respectively.
Overall the service attributes for the various hotel units are positioned very closely in the IPA map. A look at the positioning of the service attributes (room, location and staff) the one with stronger consistency in customers’ opinions is staff, as in 90% of cases appears as the most important attribute. An opposed pattern is shown for the attribute room, for which customers seem to hold more heterogeneous opinions about its importance. Overall the data suggests some inconsistency in customers’ perceptions about the importance of the service attributes. Of particular interest is the observation that there is a great variability in what regards the number of positive or negative comments. Most of the hotels exhibit a value for the performance measure (i.e. positive comments divided by the sum of positive and negative comments) not very distant from 0.5, therefore suggesting the existence of some level of service inconsistency across customers, a characteristic that is rather undesirable in service settings. The proposed analysis is susceptible of being conducted at a more fine grained level, i.e. in this case, for each hotel (see for example Figure 3).
Modified IPA displaying in detail the positioning of the three salient attributes [room, location and staff] for a single hotel unit (Hotel Afonso V).
This study, although exploratory and restricted to a small sample of service providers, from a specific service context—hotels—offers an illustrative insight of how existing managerial analytical tools can be adapted to help making sense of large volume of customer generated content. Whereas the study was applied in the context of hotel services, it is clear that the principles of the tool are applicable to any service industry, given that there is some kind of customer content to work with. Customer reviews are proliferating across service websites, platforms and social media contexts, therefore providing an ample and rich field for the development of new approaches to develop knowledge about service quality. The study illustrates that is possible to apply tools to offer a concise and structured view of the content generated by customers in their service reviews, and therefore to extract value from this abundant source of information. The extracted service attributes (room, location and staff) are particular to this study, its context and the limitations of sample selection, not meaning that they are the overall more important in the hotel industry. In order to do so, the study would have to be extended to a wider sample, and account for any conditioning variables (e.g. seasonality, weather, customer experience, etc.). As such this work suggested that there is a vast array of models and tools for assessing service quality that can be called to help make sense of the overwhelming volume of eWOM.
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