Investigating the prognostic value of KCNN4 gene expression in human pancreatic adenocarcinoma by bioinformatic analysis

Investigating the prognostic value of KCNN4 gene expression in human pancreatic adenocarcinoma by bioinformatic analysis | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Investigating the prognostic value of KCNN4 gene expression in human pancreatic adenocarcinoma by bioinformatic analysis Syed Sajidul Islam , Md. Mehedi Hasan Tushar , View ORCID Profile Bishajit Sarkar , Ripa Moni , Umme Salma Zohora , Mohammad Shahedur Rahman doi: https://doi.org/10.1101/2025.04.26.650766 Syed Sajidul Islam 1 Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University , Dhaka-1342, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Md. Mehedi Hasan Tushar 1 Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University , Dhaka-1342, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Bishajit Sarkar 1 Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University , Dhaka-1342, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Bishajit Sarkar Ripa Moni 1 Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University , Dhaka-1342, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Umme Salma Zohora 1 Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University , Dhaka-1342, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: zohoraus{at}bgeju.edu.bd rahmanms{at}bgeju.edu.bd Mohammad Shahedur Rahman 1 Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University , Dhaka-1342, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: zohoraus{at}bgeju.edu.bd rahmanms{at}bgeju.edu.bd Abstract Full Text Info/History Metrics Preview PDF Abstract Finding accurate biomarkers for early detection and prognosis is critical because pancreatic adenocarcinoma (PAAD) is a deadly cancer with a poor prognosis. Though its function in PAAD is still unknown, the gene KCNN4 , which codes for a calcium-activated potassium channel, has been linked to a number of malignancies. In this work, the cancer studies of the CPTAC, TCGA, and GTEx projects were targeted using a thorough database mining technique. Several analytical methods were used to examine full-scale molecular, expression, and prognostic profiles of the KCNN4 gene in pancreatic adenocarcinoma tissues. It was discovered that the majority of the cancerous tissue had different levels of mRNA and protein expression for this gene. The results of comparative immunohistochemistry also revealed that normal pancreatic tissues had reduced expression of the KCNN4 protein. An analysis overview of copy-number alterations and KCNN4 mutations in PAAD samples was also conducted. Furthermore, there was a correlation found between the expression of KCNN4 and both overall and disease-free survival in pancreatic adenocarcinoma. In pancreatic adenocarcinoma tissue, co-expressed genes of KCNN4 were found to be involved in cell maintenance-related functions, according to gene coexpression, additional ontology, and pathway analysis. When it comes to cancer diagnosis and treatment, the experimental findings of this study should aid in integrating KCNN4 into clinical applications. 1. Introduction 1.1 The global prevalence of cancer Cancer is a disease characterized by abnormal metabolism and signaling, which allows transformed cells to divide uncontrollably and survive. Numerous chemicals, elements, and circumstances have been identified as fundamental contributors to the onset and development of the disease ( Upadhyay, 2021 ). One of the most deadly groups of diseases affecting humans, it causes millions of deaths worldwide every year and exhibits a wide range of characteristic clinical features. These disease groups include over a hundred genetically distinct conditions that have certain similarities in their molecular mechanisms and metabolic changes ( Lambert et al., 2017 ; Vander Heiden & DeBerardinis, 2017 ). Cancer is a growing global health concern that presents significant diagnostic and therapeutic challenges. According to the World Health Organization (WHO), cancer will be the leading cause of death worldwide in 2020, accounting for approximately 10 million deaths ( de Martel et al., 2020 ; Ferlay et al., 2020 ; World Health Organization, 2023 ). The most prevalent kinds are stomach, colorectal, lung, prostate, and skin (non-melanoma) cancers ( Siegel et al., 2018 ). The growing rate of cancer is caused by several factors, such as changing lifestyles, aging populations, and environmental exposures. Growing older is a significant risk factor because it increases the chance of getting cancer because genetic mutations accumulate over time ( Islami et al., 2018 ). Additionally, a person’s risk of developing cancer is greatly increased by lifestyle choices like smoking, drinking alcohol, eating poorly, and not exercising ( Torre et al., 2016 ). Pancreatic cancer is the 12th most frequent cancer and ranks sixth in terms of fatality rates worldwide in both sexes, according to GLOBOCAN 2022 estimates. According to reports, North America, Europe, and Australia-New Zealand have the highest occurrence rates of cancer ( Bray et al., 2024 ). From 1991 onward, pancreatic cancer incidence and mortality increased in practically every country in the world ( Ilic & Ilic, 2022 , 2024 ). Conversely, only Canada and Mexico reported favorable trends in pancreatic cancer mortality. According to a comparative mortality study conducted across 28 European Union countries, pancreatic cancer is expected to overtake breast cancer by 2025 (i.e., there will be a 25% increase in pancreatic cancer deaths over breast cancer deaths), placing it on the third position of the most frequent cause of mortality from cancer by that time (after colorectal and lung cancer) ( Ferlay et al., 2016 ). Download figure Open in new tab Fig 1: The age-standardized rate of pancreatic cancer incidence by sex and the rates specific to a certain region are shown in this column graph. The world age-standardized rate for males is shown in descending order, with the highest national rates for both males and females superimposed. (Source: GLOBOCAN 2022) ( Bray et al., 2024 ) Early cancer diagnosis is essential for better survival rates and efficient treatment, but it is still very difficult. Screening programs and other early detection techniques vary in their accessibility and efficacy. For instance, it has been demonstrated that mammography for breast cancer and colonoscopy for colorectal cancer lower death rates; however, there are differences in the accessibility of these tests, especially in low- and middle-income nations ( Jemal et al., 2006 ). Furthermore, some cancers—like pancreatic cancer—don’t have good early detection techniques, which frequently leads to late-stage diagnoses and dismal prognoses ( Rahib et al., 2014 ). 1.2 Biological functions of the KCNN4 gene The calcium-activated potassium channel protein with intermediate conductance is encoded by the KCNN4 gene, also referred to as KCa3.1. Numerous tissues, including hematopoietic cells, epithelial cells, and the vascular endothelium, exhibit high levels of expression for this channel. It is essential for many physiological functions, most notably the control of intracellular calcium signaling and membrane potential. The control of potassium ion flow in response to intracellular calcium levels is the principal biological role of the KCNN4 channel. Membrane hyperpolarization results from the opening of the KCNN4 channel, which permits potassium ions to leave the cell in response to an increase in intracellular calcium. In turn, this hyperpolarization affects a number of cellular processes, including the control of cell volume, proliferation, and migration ( Feske et al., 2015 ; Joiner et al., 1997 ; Wei et al., 2005 ).s KCNN4 channels are essential for maintaining ionic homeostasis because they allow the efflux of K+ ions in response to increases in intracellular Ca2+ concentrations. Numerous physiological processes, including migration, proliferation, and regulation of cell volume, depend on this mechanism to function appropriately ( Faber & Sah, 2003 ). For example, in erythrocytes, KCNN4 mediates K+ efflux, which is essential for these cells to survive under osmotic stress and helps maintain cell volume and shape ( Hoffman et al., 2003 ). Activation and proliferation of T lymphocytes in the immune system are regulated by the expression of KCNN4 channels. The channel is essential to immune responses because its activity maintains the Ca2+ signaling required for T-cell activation and cytokine production ( Wulff et al., 2000 ). 1.3 KCNN4 in the oncogenic processes Current research has demonstrated KCNN4 ’s role in a number of oncogenic processes. Numerous cancer types have been linked to the channel’s involvement in the invasion, migration, and multiplication of cancer cells. It seems essential to the survival and aggressive behavior of cancer cells for it to keep the ionic balance within them ( George Chandy et al., 2004 ). In pancreatic cancer, KCNN4 contributes to the aggressive characteristics of cancer cells. By preserving the ionic homeostasis necessary for these functions, the channel’s activity promotes the continuous growth and survival of pancreatic cancer cells ( Jäger et al., 2004 ). Furthermore, KCNN4 affects how cancer cells interact with their surroundings, which promotes the growth and metastasis of tumors ( Jensen et al., 2002 ; Ohya & Kito, 2018 ). 1.4 Objectives of the study To investigate the potential oncogenic roles and clinical implications of KCNN4 gene expression in human pancreatic adenocarcinoma (PAAD). To evaluate their expression pattern, methylation, and mutation status as well as their overall impact on cancer patients’ survival. To guide the upcoming clinical research on KCNN4 and its byproducts for the purpose of developing new cancer treatments and diagnostic tools. 2. Materials and Methods 2.1 Analysis of expression of KCNN4 in various normal tissue and cancerous tissue types Two different online based tools, i.e., GEPIA2 ( http://gepia2.cancer-pku.cn/#index ), and GENT2 ( http://gent2.appex.kr/ ), were utilized to investigate the different expressions pattern of KCNN4 across a variety of normal calls and cancer cells (Park et al., 2019, p. 2; Tang et al., 2017 ). A tool for various transcriptional analyses, such as differential-expression analysis and correlation in a variety of cancerous and normal tissues, is GEPIA2, which is built-in RNA-sequencing expression data from the GTEx and the TCGA projects, comprising 8,587 normal samples and 9,736 tumors. ( Tang et al., 2017 ). During the analysis with the GEPIA2 server, default values for the parameters were used. On the other hand, GENT2 offers expression pattern analysis across 72 different tissues and comprises over 68,000 samples, making it a more valuable platform for prognostic analysis of targeted genes (Park et al., 2019). 2.2 KCNN4 expression pattern optimization in normal and pancreatic adenocarcinoma (PAAD) tissue Three web-based tools were utilized in this method, i.e., GEPIA2 server, UALCAN server ( https://ualcan.path.uab.edu ), and the HPA server ( www.proteinatlas.org ) ( Chandrashekar et al., 2017 ; Pontén et al., 2008 ; Tang et al., 2017 ). Using a combination of TCGA and GTEx datasets, the GEPIA2 web-server was utilized to compare the differences in KCNN4 gene expression between the normal tissues and those affected by pancreatic adenocarcinoma. An integrated, interactive resource is the UALCAN web server which is built on several widely accessible OMICS databases. It is useful for a variety of tasks, such as facilitating the interpretation of expression profiles, demonstrating patient survival characteristics, and controlling gene expression through epigenetic regulation. As with the prior step, we used this web server to determine our target genes’ expression profile in the normal tissue and pancreatic adenocarcinoma (PAAD) tissue. Through the combination of several sets of omics technologies, like transcriptomics, mass spectrometry (MS) based proteomics, antibody-based imaging, and systems biology, the Human Protein Atlas (HPA) facilitates the investigation of the human proteome ( Pontén et al., 2008 ). Using the HPA server, a graphic assessment of the histological samples (HPA053841) among the normal and pancreatic adenocarcinoma (PAAD) tissue was produced. In this step, every experiment was conducted using the default parameters, with a p value of less than 0.05 being considered important. 2.3 Determining the pattern of methylation in DNA and KCNN4 promoter in pancreatic adenocarcinoma (PAAD) UALCAN web server was utilized to search for variations throughout the KCNN4 gene’s promoter-methylation pattern in both normal and pancreatic tumor tissues. After that, GDC TCGA Pancreatic Cancer (PAAD) samples (n=223) had been selected as the basis sample set, and using the UCSC-Xena web browser, the gene’s DNA methylation-pattern in PAAD tissues was determined ( Chandrashekar et al., 2017 ; Goldman et al., 2017 ). We selected genomic data type of the KCNN4 gene utilizing gene expression, copy number, and somatic mutation dataset, while we left the other experiments parameters at their initial settings. Web-based tools for clinical and phenotypic annotation of a desired gene are provided by the UCSC Xena platform. With the addition of over 1500 datasets covering 50 distinct cancer types, this multi-omics database integration is enhanced. Along with gene expression, copy number, and somatic mutation analysis, the neoplasm histologic grade, disease type, and age at initial pathogenesis diagnosis was also analyzed in PAAD samples. 2.4 Analyzing the mutations in KCNN4 and variations in copy numbers in pancreatic adenocarcinoma samples The KCNN4 gene’s mutations and copy-number alterations were computed using the cBioPortal ( www.cbioportal.org ) web-based server (J. Gao et al, 2013 , 2018 ; Jiao et al., 2019 ). It is an open access, web-based translational research platform that helps reveal the genomic and epigenomic differences associated with a given gene and allows for multidirectional analysis of that gene. Over 3,609 samples or 3,569 patients were examined in 13 different pancreatic cancer studies, and the server chose samples from among those deposited by the MSK, TCGA, QCMG, and CPTAC to look into copy-number alterations and mutations. 2.5 Investigation of the associations among KCNN4 expression and clinical features of patients with pancreatic cancer Utilizing the samples of TCGA supplied by the UALCAN web-based server, the associations among the KCNN4 gene expression profile and various types of clinical characteristics of patients with pancreatic adenocarcinoma (PAAD) was ascertained ( Chandrashekar et al., 2017 ). Different expression patterns were analyzed and recorded based on the specific cancer stages, age, race, gender, smoking history, histology of tumor, nodal-metastasis status, and presence of T53 mutation of the patient. The servers’ default settings were used for the experiment, and a p value of under 0.05 was used to classify predictions as statistically important. 2.6 Evaluating the association between pancreatic cancer patients’ probable survival trend and KCNN4 expression The Kaplan-Meier plotter online server ( www.kmplot.com/analysis/ ) was utilized to establish the correlation among KCNN4 expression and the survival-rate of pancreatic cancer patients ( Nagy et al., 2018 ). More than 60,000 genes can be evaluated by this tool, including those that are involved in the expression of messenger RNA and microRNA in twenty one distinct types of cancer. Various patterns of survival, such as overall survival (OS), and disease free survival (DFS) of pancreatic cancer patients in response to KCNN4 expression, were retrieved by drawing Kaplan-Meier plots while keeping other parameters default, and the analysis was conducted on 1237 patients. Thereafter, various KCNN4 gene translational data related to pancreatic adenocarcinoma patients’ survival were also obtained from the PrognoScan ( Mizuno et al., 2009 ) web database. 2.7 identifying different genes similar to KCNN4 in pancreatic adenocarcinoma (PAAD) The mining of different genes that are fairly comparable with KCNN4 was achieved by two distinct web servers, such as the GEPIA2, and UCSC-Xena web-server. Initially, the KCNN4 gene was looked up in the GEPIA2 online database (Expression Analysis) to identify potential genes that are similar. According to related gene-clusters, the server produces Pearson correlation coefficient (PCC) values. Thereafter, the similar genes were identified with PCC scores. Furthermore, the GEPIA2 web-based server was utilized to decipher and evaluate the relationship between the genes that were identified as very similar to KCNN4 in the preceding step and the KCNN4 gene. When presenting the relationship between the two chosen genes, the GEPIA2 server generated the p-values; any p-value lower than 0.05 was considered to be statistically noteworthy. Lastly, the gene-expression patterns of the 2 chosen genes in PAAD patients were predicted using the UCSC-Xena web browser. 2.8 Interpretation of ontology terms and pathways associated with KCNN4 and its functionally related genes The Enrichr server ( https://maayanlab.cloud/Enrichr/ ) was used to find the cell signaling pathways and gene ontology (GO) of KCNN4 and potentially related genes (E. Y. Chen et al., 2013 ). This platform utilizes enrichment analysis to infer information about a particular set of genes through comparison with multiple datasets of genomics that represent previous biological knowledge. Here, we employed the KCNN4 gene and every potential gene from the preceding step that is similar to interpret various GO (gene ontology) terms, i.e., GO molecular function, GO biological processes, and GO cellular components. Subsequently, the Enrichr web-based server was utilized to extract multiple signaling pathways from the BioPlanet 2019, Reactome-2016, and KEGG 2019 Human databases. 3. Results and Discussion 3.1 Expression profile of KCNN4 in a range of cancerous and normal tissues The analysis of the GENT2 servers have detected a high expression of KCNN4 gene in Pancreatic Adenocarcinoma (PAAD) tissues, with a pronounced presence of additional cancer types, such as Skin Cutaneous Melanoma (SKCM), Bladder Carcinoma (BLCA), Prostate Adenocarcinoma (PRAD), Rectum Adenocarcinoma (READ), Colon Adenocarcinoma (COAD), Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) and so on. On the contrary, KCNN4 was found to be under-expressed in Adenoid Cystic Carcinoma (ACC) and Cholangiocarcinoma (CHOL) tumor tissues based on our findings. These results were displayed through examination of the KCNN4 gene expression patterns in the GEPIA2 ( Figure 5 ) and GENT2 servers ( Figure 6 ). Further comparisons between various cancer tissues and their corresponding normal counterparts revealed a higher expression of KCNN4 . Download figure Open in new tab Fig 5: The GEPIA2 web server showed the overexpression of KCNN4 (red) in a variety of tumor tissues. Download figure Open in new tab Fig 6: Based on the log 2-fold change in the GENT2 server, the boxplot interpretation illustrates the differences in KCNN4 expression across various cancer types. 3.2 KCNN4 expression analysis in cancerous and normal pancreatic tissues A similar investigation using the GEPIA2 server revealed results similar to the previous step, with the breast tumor samples (n = 179) exhibiting higher levels of KCNN4 expression and the median value of log2 (TPM+1) is converging around 6, in contrast to approximately 0.5 for the samples of normal pancreatic tissues (n= 171) ( Figure 7 ). Once more, the analytical report on the TCGA samples obtained from the UALCAN web server indicated that breast tumor tissues (n=178) had higher levels of KCNN4 expression than normal tissues (n=4) ( Figure 8 ). Subsequently, an analysis was conducted using the HPA server to compare the expressions of KCNN4 protein levels in normal and cancerous pancreatic tissues by immunohistochemistry (IHC). The results showed that normal tissues exhibited no staining and a negative intensity of the immunohistochemistry test, while pancreatic cancer tissue had a weak assay intensity and no staining ( Figures 9a and 9b ). These assumptions reinforced the results of earlier investigations that indicated pancreatic cancer tissues expressed KCNN4 slightly, both at the mRNA and protein levels, compared to the normal tissues. Download figure Open in new tab Fig 7: Investigation in the GEPIA2 server revealed that pancreatic adenocarcinoma (PAAD) samples had higher KCNN4 expression than normal breast tissues (the red box indicates PAAD samples, the black box indicates adjacent normal tissue samples) Download figure Open in new tab Fig 8: The UALCAN database also indicated that KCNN4 expressed at a higher level in TCGA PAAD samples compared to nearby normal pancreatic tissue s. the analytical report indicated that breast tumor tissues (n=178) had higher levels of KCNN4 expression than normal tissues (n=4). Download figure Open in new tab Fig 9: The results of comparative immunohistochemistry also revealed that normal pancreatic tissues had reduced expression of the KCNN4 protein. Moreover, as demonstrated by differing staining intensities from the HPA database, comparative immunohistochemistry observation revealed reduced KCNN4 protein expression in normal breast tissues (a) compared to pancreatic cancer tissues (b) . 3.3 Analysis of the KCNN4 promoter and DNA-methylation in healthy and diseased pancreatic tissue Investigation of the promoter methylation of the KCNN4 gene by the UALCAN web server in the TCGA samples suggested that there may be more hypomethylation of the gene found in tumor specimens (n=184) than in normal specimens (n=10) ( Figure 10 ). This finding suggests that KCNN4 overexpression in pancreatic cancer patients may be related to this, since the continuous activation of the gene is fueled by hypomethylation in the CpG-island of promoters. Download figure Open in new tab Fig 10: Investigation of the promoter of the KCNN4 gene and DNA methylation in samples of pancreatic cancer. The UALCAN server revealed the KCNN4 promoter’s hypomethylation sign. Web-based tools for clinical and phenotypic annotation of a desired gene are provided by the UCSC Xena platform. The UCSC Xena browser determined the gene expression, copy numbers, and the KCNN4 gene’s somatic mutations in the GDC TCGA Pancreatic Cancer (PAAD) samples (n=223). Moreover, we also analyzed the neoplasm histologic grade, disease type, and age at initial pathogenesis diagnosis in pancreatic adenocarcinoma samples ( Figure 11 ). From this analysis, we found that the primary tumor was 83%, solid tissue normal was 16.6%, and metastasis was 0.442% among all the samples (n=223). Download figure Open in new tab Fig 11: UCSC Xena browser analyzed the gene expression, copy numbers, and the KCNN4 gene’s somatic mutations in the GDC TCGA Pancreatic Cancer (PAAD) samples. Among the GDC TCGA Pancreatic Cancer (PAAD) samples the ductal and lobular neoplasms were 81.6%, adenomas and adenocarcinomas 15.2%, cystic, mucinous and serous neoplasm was 2.69%, epithelial neoplasms was 0.448% ( Figure 12 ). A bar chart was formed, wherein the x axis denoted the neoplasm histologic grad and the y axis denoted the age at initial pathologic diagnosis ( Figure 13 ). It was found that neoplasm histologic grade-2 was initially diagnosed at the age of 65 (median). And neoplasm histologic grade-1, grade-3, and grade-4 were initially diagnosed at the age 65, 67, 74 (median) respectively. Download figure Open in new tab Fig 12: Analysis of the neoplasm histologic grade, disease type, and age at initial pathogenesis diagnosis in PAAD samples by the UCSC Xena browser. Download figure Open in new tab Fig 13: The bar chart represents the relation among histologic grades and initial diagnosis age. 3.4 Analyzing the KCNN4 genes’ copy numbers alteration and mutation frequencies in pancreatic cancer specimens In pancreatic cancer research, copy numbers alteration and mutations analysis of the KCNN4 gene showed the existence of two somatic mutations with a percent mutation-frequency of 0.2 in all of the pancreatic cancer samples that were chosen for assessment (Tab 1). Of the various kinds of mutations found in the pancreatic cancer study samples, such as amplification, deep-deletion, and nonsense, the missense mutations were the most common form (2) (Tab 1). On chromosome 19, every mutation fell between 44278467 bp (start) and 44280710 bp (end), in charge of encoding the KCNN4 protein, which has 427 amino acids ( Fig 14 and Table 1 ). The pancreatic cancer sample (UTSW) showed the highest alteration frequency; in 14.68% of the 109 cases, the gene was altered. The gene was changed in 2.72% of the 184 cases in the pancreatic adenocarcinoma (TCGA) sample; of these, 0.54% (1 case) had a mutation and 2.17% (4 cases) had an amplification. Finally, the gene changed in 1.02% of the 98 cases of pancreatic neuroendocrine tumors. When combined, these genetic differences appear to be important factors in the prognosis of pancreatic adenocarcinoma (PAAD) ( Fig 15 ). View this table: View inline View popup Download powerpoint Table 1: Summary of the KCNN4 gene mutations and copy numbers alteration analysis in pancreatic cancer samples Download figure Open in new tab Fig 14: The frequency of copy number alteration and KCNN4 mutation in various pancreatic cancer research. A lollipop diagram showing the common mutations found in pancreatic cancer samples’ KCNN4 gene. Download figure Open in new tab Fig 15: Bar diagram showing the various patterns of genetic variations in the KCNN4 gene that has been discovered in a number of studies on pancreatic cancer. 3.5 Relationship between pancreatic cancer patients’ clinical characteristics and KCNN4 gene expression With the help of the UALCAN server, the association between various clinical characteristics of patients with pancreatic cancer, such as age, sex, race, and KCNN4 expression, was assessed using the TCGA sample ( Table 2 and Figure 16 ). The most noticeable overexpression was observed in tumor grade 2 (p =7.005700E-02) in relation to other tumor-grades found in the TCGA specimens ( Figure 16e ). Significant and varying levels of KCNN4 expression were also observed in all the chosen clinical characteristics of patients with pancreatic cancer. Remarkably, across the age ranges, it was discovered that middle-aged patients (41–60 years) expressed more KCNN4 than younger (21-40) and old-age patients (61-100 years) ( Figure 16d ). It was also discovered that expression increased markedly as the cancer stage progressed, peaking at stage-4 of pancreatic adenocarcinoma (PAAD) ( Figure 16a ). Men showed higher levels of KCNN4 expression than women in terms of gender-specific stratification. ( Figure 16c ). Furthermore, compared to patients of other racial categories, Asians displayed a higher degree of expression. Furthermore, compared to TP53 non mutant pancreatic cancer patients, TP53 mutant pancreatic cancer patients were found to express higher levels of KCNN4 . Taken together, these results indicate that variations in KCNN4 expression patterns possibly important in how the cancer prognosis manifests and, as a result, positively correlate with various clinical characteristics of patients with pancreatic cancer. View this table: View inline View popup Table 2: An analysis overview of copy-number alterations and KCNN4 mutations in PAAD samples Download figure Open in new tab Download figure Open in new tab Download figure Open in new tab Download figure Open in new tab Fig 16: Boxplot showing the relationship between multiple clinical features of pancreatic adenocarcinoma (PAAD) patients and KCNN4 gene expression. The following factors were analyzed: (a) stage of cancer; (b) race of patients; (c) gender of patients; (d) age of patients; (e) grade of tumor; (f) nodal-metastasis; and (g) status of TP53 mutation. KCNN4 expression was found to be elevated in all of the needed clinical parameters. 3.6. The survival trend of patients with pancreatic cancer in the response to KCNN4 Expression Variations in patient survival rates with pancreatic cancer following the expression of KCNN4 are shown by Kaplan-Meier (KM) plots in Figure 17 . According to the analysis, there is a negative correlation between the higher expression of KCNN4 and pancreatic cancer patients’ overall-survival (OS), utilizing a hazard ratio (HR) of 1.19 (p=0.0165) ( Figure 17a ). Similar types of findings regarding disease-free survival (DFS) were also made (HR=0.57; p=<4.37*10 -05 ) ( Figure 17b ). The results showed that disease-free survival (DFS) patients had a lower survival rate than overall-survival OS patients, with a median life expectancy of 60–120 months. When considered collectively, these collected data indicate that increased KCNN4 expression may be linked to a decreased life expectancy in pancreatic cancer patients and may be a predictor of their survival status. Download figure Open in new tab Fig 17: Kaplan-Meier plots illustrating the predicted survival trend of patients with PAAD versus KCNN4 expression. (a) Overall survival; (b) Disease free survival. There was a negative correlation between the expression of KCNN4 and the different survival rates of PAAD patients. 3.7 Analysis of genes functionally similar to KCNN4 in pancreatic adenocarcinoma Understanding the KCNN4 ’s fundamental regulatory mechanism in pancreatic adenocarcinoma cells, the PAAD sample in the GEPIA2 server was used to carry out similar gene detection in order to find functionally related genes. PPP1R13L (protein phosphatase 1 regulatory subunit 13-like) was discovered as the most likely gene that was similar in various pancreatic adenocarcinoma tissues with a Pearson Correlation Coefficient (PCC) of 0.81 ( Table 3 ). View this table: View inline View popup Table 3: Similar genes with KCNN4 in PAAD tumor sample from the GEPIA2 server database and ranked them based on their Pearson correlation coefficient (PCC). Another comparable finding was also made utilizing the GEPIA2 co-expression analysis, which indicated that the gene ( PPP1R13L ) had a 0.81 (p=0) correlation coefficient and was positively co-expressed in PAAD tissues ( Figure 18a ). Among the other functionally similar genes, VASP , CBLC , and GJB3 additionally revealed that the level of KCNN4 gene expression in pancreatic adenocarcinoma tissues correlated positively (PCC:> 0.70) ( Figure 18b , 18c, 18d). Download figure Open in new tab Download figure Open in new tab Fig 18: Analysis of co-expression of KCNN4 and PPP1R13L genes using the GEPIA2 database ( Fig 18a ). Analysis of co-expression of KCNN4 and VASP genes using the GEPIA2 database ( Fig 18b ). Analysis of co-expression of KCNN4 and CBLC genes using the GEPIA2 database ( Fig 18c ). Analysis of co-expression of KCNN4 and GJB3 genes using the GEPIA2 database ( Fig 18d ) 3.8 Analysis of KCNN4 co-expressed gene functional enrichment in PAAD tissues Enrichr web server was used to understand the gene ontologies (GO), which are biological processes, molecular functions, cellular components, and pathways associated with the co-expressed KCNN4 genes in the pancreatic cancer specimens from the prior step. Analysis of the GO discovered that the majority of the genes have a role in controlling positive regulations of cell differentiation, regulation of ruffle assembly, negative regulation of protein polymerization, regulation of epidermal growth factor receptor signaling pathway, negative regulation of supramolecular fiber organization, cadherin binding, actin binding, and SH3 domain binding ( Figures 19a and 19c ). Furthermore, the majority of the co-expressed genes of the KCNN4 in PAAD tissues were found to be primarily involved in focal adhesion, cell-cell junction, cell-substrate junction, and connexin complex, according to cellular component analysis ( Figure 19b ). Several pathway analyses, including the Reactome, KEGG, and BioPlanet pathways, were also conducted using the co-expressed genes. The co-expressed genes’ pathway analysis showed that they are primarily in charge of maintaining the TGF-beta regulation of extracellular matrix, integrin signaling pathway, mitochondrial pathway of apoptosis, axon guidance, Rap1 signaling pathway. Cellular senescence, Ras signaling pathway, developmental biology R-HSA-1266738, and so on ( Figure 19d , 19e, and 19f). Download figure Open in new tab Download figure Open in new tab Download figure Open in new tab Fig 19: The results of the analysis of signaling pathways and gene ontology (GO). Gene ontology- (a) GO biological processes, (b) GO cellular compartment and pathway, (c) GO molecular function, (d) BioPlanet-2019, (e) KEGG-2019 human, (f) Reactome-2016 analysis of the co-expressed genes of KCNN4 in PAAD specimens. 4. Conclusion Comparing cancerous pancreatic adenocarcinoma tissues to nearby normal tissues, this study found that KCNN4 expression is significantly higher in the former. Further analysis of abnormal promoter methylation patterns and KCNN4 mutations may help to explain the inconsistent clinical findings of patients due to gene dysregulation with pancreatic cancer. Moreover, elevated KCNN4 expression levels were linked to lower patient survival. It was discovered that PPP1R13L and other KCNN4 genes with comparable functions were involved in processes linked to the development of pancreatic adenocarcinoma (PAAD) in pancreatic cancer tissues. When considered collectively, the data from this investigation and other research seem to support the possibility that KCNN4 could serve as a predictive biomarker for pancreatic adenocarcinoma (PAAD). The scientific results of this investigation ought to direct future clinical research on therapeutic and diagnostic approaches based on KCNN4 for the detection and management of pancreatic cancer. Even though there have been great advancements in the knowledge and treatment of pancreatic cancer, more research and innovation are still required given the disease’s rising prevalence and its difficult diagnostic and therapeutic cases. Reducing the global cancer burden requires addressing disparities in access to screening and treatment, enhancing early detection techniques, and creating novel, potent treatments. References Abdin , S. , Zaher , D. , Arafa , E.-S. , & Omar , H . ( 2018 ). Tackling Cancer Resistance by Immunotherapy: Updated Clinical Impact and Safety of PD-1/PD-L1 Inhibitors . Cancers , 10 ( 2 ), 32 . doi: 10.3390/cancers10020032 OpenUrl CrossRef PubMed Abe , T. , Blackford , A. L. , Tamura , K. , Ford , M. , McCormick , P. , Chuidian , M. , Almario , J. A. , Borges , M. , Lennon , A. M. , Shin , E. J. , Klein , A. P. , Hruban , R. H. , Canto , M. I. , & Goggins , M . ( 2019 ). Deleterious Germline Mutations Are a Risk Factor for Neoplastic Progression Among High-Risk Individuals Undergoing Pancreatic Surveillance . Journal of Clinical Oncology , 37 ( 13 ), 1070 – 1080 . doi: 10.1200/JCO.18.01512 OpenUrl CrossRef PubMed Argentiero , A. , Calabrese , A. , Solimando , A. G. , Notaristefano , A. , Panarelli , M. M. G. , & Brunetti , O . ( 2019 ). Bone metastasis as primary presentation of pancreatic ductal adenocarcinoma: A case report and literature review . Clinical Case Reports , 7 ( 10 ), 1972 – 1976 . doi: 10.1002/ccr3.2412 OpenUrl CrossRef PubMed Assenat , E. , Mineur , L. , Mollevi , C. , Lopez-Crapez , E. , Lombard-Bohas , C. , Samalin , E. , Portales , F. , Walter , T. , de Forges , H. , Dupuy , M. , Boissière-Michot , F. , Ho-Pun-Cheung , A. , Ychou , M. , & Mazard , T . ( 2021 ). Phase II study evaluating the association of gemcitabine, trastuzumab and erlotinib as first-line treatment in patients with metastatic pancreatic adenocarcinoma (GATE 1) . International Journal of Cancer , 148 ( 3 ), 682 – 691 . doi: 10.1002/ijc.33225 OpenUrl CrossRef PubMed Australian Pancreatic Cancer Genome Initiative , Waddell , N. , Pajic , M. , Patch , A.-M. , Chang , D. K. , Kassahn , K. S. , Bailey , P. , Johns , A. L. , Miller , D. , Nones , K. , Quek , K. , Quinn , M. C. J. , Robertson , A. J. , Fadlullah , M. Z. H. , Bruxner , T. J. C. , Christ , A. N. , Harliwong , I. , Idrisoglu , S. , Manning , S. , … Grimmond , S. M. ( 2015 ). Whole genomes redefine the mutational landscape of pancreatic cancer . Nature , 518 ( 7540 ), 495 – 501 . doi: 10.1038/nature14169 OpenUrl CrossRef PubMed Avula , L. R. , Hagerty , B. , & Alewine , C . ( 2020 ). Molecular mediators of peritoneal metastasis in pancreatic cancer . Cancer and Metastasis Reviews , 39 ( 4 ), 1223 – 1243 . doi: 10.1007/s10555-020-09924-4 OpenUrl CrossRef PubMed Bailey , P. , Chang , D. K. , Nones , K. , Johns , A. L. , Patch , A.-M. , Gingras , M.-C. , Miller , D. K. , Christ , A. N. , Bruxner , T. J. C. , Quinn , M. C. , Nourse , C. , Murtaugh , L. C. , Harliwong , I. , Idrisoglu , S. , Manning , S. , Nourbakhsh , E. , Wani , S. , Fink , L. , Holmes , O. , … Grimmond , S. M . ( 2016 ). Genomic analyses identify molecular subtypes of pancreatic cancer . Nature , 531 ( 7592 ), 47 – 52 . doi: 10.1038/nature16965 OpenUrl CrossRef PubMed Beans , C . ( 2018 ). Targeting metastasis to halt cancer’s spread . Proceedings of the National Academy of Sciences , 115 ( 50 ), 12539 – 12543 . doi: 10.1073/pnas.1818892115 OpenUrl FREE Full Text Beltrami , A. , Hilliard , A. , & Green , A. L . ( 2022 ). Demographic and socioeconomic disparities in pediatric cancer in the United States: Current knowledge, deepening understanding, and expanding intervention . Cancer Epidemiology , 76 , 102082 . doi: 10.1016/j.canep.2021.102082 OpenUrl CrossRef Biasiotta , A. , D’Arcangelo , D. , Passarelli , F. , Nicodemi , E. M. , & Facchiano , A . ( 2016 ). Ion channels expression and function are strongly modified in solid tumors and vascular malformations . Journal of Translational Medicine , 14 ( 1 ), 285 . doi: 10.1186/s12967-016-1038-y OpenUrl CrossRef PubMed Billan , S. , Kaidar-Person , O. , & Gil , Z . ( 2020 ). Treatment after progression in the era of immunotherapy . The Lancet Oncology , 21 ( 10 ), e463 – e476 . doi: 10.1016/S1470-2045(20)30328-4 OpenUrl CrossRef PubMed ↵ Bray , F. , Laversanne , M. , Sung , H. , Ferlay , J. , Siegel , R. L. , Soerjomataram , I. , & Jemal , A . ( 2024 ). Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries . CA: A Cancer Journal for Clinicians , 74 ( 3 ), 229 – 263 . doi: 10.3322/caac.21834 OpenUrl CrossRef Bulk , E. , Ay , A.-S. , Hammadi , M. , Ouadid-Ahidouch , H. , Schelhaas , S. , Hascher , A. , Rohde , C. , Thoennissen , N. H. , Wiewrodt , R. , Schmidt , E. , Marra , A. , Hillejan , L. , Jacobs , A. H. , Klein , H.-U. , Dugas , M. , Berdel , W. E. , Müller-Tidow , C. , & Schwab , A . ( 2015 ). Epigenetic dysregulation of K Ca 3.1 channels induces poor prognosis in lung cancer: K Ca 3.1 channel and poor lung cancer prognosis . International Journal of Cancer , 137 ( 6 ), 1306 – 1317 . doi: 10.1002/ijc.29490 OpenUrl CrossRef PubMed Burris , H. A. , Moore , M. J. , Andersen , J. , Green , M. R. , Rothenberg , M. L. , Modiano , M. R. , Cripps , M. C. , Portenoy , R. K. , Storniolo , A. M. , Tarassoff , P. , Nelson , R. , Dorr , F. A. , Stephens , C. D. , & Von Hoff , D. D. ( 1997 ). Improvements in survival and clinical benefit with gemcitabine as first-line therapy for patients with advanced pancreas cancer: A randomized trial . Journal of Clinical Oncology , 15 ( 6 ), 2403 – 2413 . doi: 10.1200/JCO.1997.15.6.2403 OpenUrl Abstract / FREE Full Text Buscail , L. , Bournet , B. , & Cordelier , P . ( 2020 ). Role of oncogenic KRAS in the diagnosis, prognosis and treatment of pancreatic cancer . Nature Reviews Gastroenterology & Hepatology , 17 ( 3 ), 153 – 168 . doi: 10.1038/s41575-019-0245-4 OpenUrl CrossRef PubMed Cai , J. , Chen , H. , Lu , M. , Zhang , Y. , Lu , B. , You , L. , Zhang , T. , Dai , M. , & Zhao , Y . ( 2021 ). Advances in the epidemiology of pancreatic cancer: Trends, risk factors, screening, and prognosis . Cancer Letters , 520 , 1 – 11 . doi: 10.1016/j.canlet.2021.06.027 OpenUrl CrossRef PubMed Callery , M. P. , Chang , K. J. , Fishman , E. K. , Talamonti , M. S. , William Traverso , L. , & Linehan , D. C . ( 2009 ). Pretreatment Assessment of Resectable and Borderline Resectable Pancreatic Cancer: Expert Consensus Statement . Annals of Surgical Oncology , 16 ( 7 ), 1727 – 1733 . doi: 10.1245/s10434-009-0408-6 OpenUrl CrossRef PubMed Capasso , M. , Franceschi , M. , Rodriguez-Castro , K. I. , Crafa , P. , Cambiè , G. , Miraglia , C. , Barchi , A. , Nouvenne , A. , Leandro , G. , Meschi , T. , de’ Angelis , G. L. , & Di Mario , F. ( 2018 ). Epidemiology and risk factors of pancreatic cancer . Acta Bio Medica Atenei Parmensis , 89 (9-S), 141 – 146 . doi: 10.23750/abm.v89i9-S.7923 OpenUrl CrossRef PubMed Chalabi-Dchar , M. , Cassant-Sourdy , S. , Duluc , C. , Fanjul , M. , Lulka , H. , Samain , R. , Roche , C. , Breibach , F. , Delisle , M.-B. , Poupot , M. , Dufresne , M. , Shimaoka , T. , Yonehara , S. , Mathonnet , M. , Pyronnet , S. , & Bousquet , C . ( 2015 ). Loss of Somatostatin Receptor Subtype 2 Promotes Growth of KRAS-Induced Pancreatic Tumors in Mice by Activating PI3K Signaling and Overexpression of CXCL16 . Gastroenterology , 148 ( 7 ), 1452 – 1465 . doi: 10.1053/j.gastro.2015.02.009 OpenUrl CrossRef PubMed ↵ Chandrashekar , D. S. , Bashel , B. , Balasubramanya , S. A. H. , Creighton , C. J. , Ponce-Rodriguez , I. , Chakravarthi , B. V. S. K. , & Varambally , S . ( 2017 ). UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses . Neoplasia , 19 ( 8 ), 649 – 658 . doi: 10.1016/j.neo.2017.05.002 OpenUrl CrossRef PubMed Chen , D. S. , & Mellman , I . ( 2013 ). Oncology Meets Immunology: The Cancer-Immunity Cycle . Immunity , 39 ( 1 ), 1 – 10 . doi: 10.1016/j.immuni.2013.07.012 OpenUrl CrossRef PubMed Web of Science ↵ Chen , E. Y. , Tan , C. M. , Kou , Y. , Duan , Q. , Wang , Z. , Meirelles , G. V. , Clark , N. R. , & Ma’ayan , A . ( 2013 ). Enrichr: Interactive and collaborative HTML5 gene list enrichment analysis tool . BMC Bioinformatics , 14 ( 1 ), 128 . doi: 10.1186/1471-2105-14-128 OpenUrl CrossRef PubMed Chen , S. , Su , X. , & Mo , Z . ( 2022 ). KCNN4 is a Potential Biomarker for Predicting Cancer Prognosis and an Essential Molecule that Remodels Various Components in the Tumor Microenvironment: A Pan-Cancer Study . Frontiers in Molecular Biosciences , 9 , 812815 . doi: 10.3389/fmolb.2022.812815 OpenUrl CrossRef Chen , Y. , Bai , X. , Zhang , Q. , Wen , L. , Su , W. , Fu , Q. , Sun , X. , Lou , Y. , Yang , J. , Zhang , J. , Chen , Q. , Wang , J. , & Liang , T . ( 2016 ). The hepatitis B virus X protein promotes pancreatic cancer through modulation of the PI3K/AKT signaling pathway . Cancer Letters , 380 ( 1 ), 98 – 105 . doi: 10.1016/j.canlet.2016.06.011 OpenUrl CrossRef PubMed Christenson , E. S. , Jaffee , E. , & Azad , N. S . ( 2020 ). Current and emerging therapies for patients with advanced pancreatic ductal adenocarcinoma: A bright future . The Lancet Oncology , 21 ( 3 ), e135 – e145 . doi: 10.1016/S1470-2045(19)30795-8 OpenUrl CrossRef PubMed Cicenas , J. , Kvederaviciute , K. , Meskinyte , I. , Meskinyte-Kausiliene , E. , Skeberdyte , A. , & Cicenas , J . ( 2017 ). KRAS, TP53, CDKN2A, SMAD4, BRCA1, and BRCA2 Mutations in Pancreatic Cancer . Cancers , 9 ( 5 ), 42 . doi: 10.3390/cancers9050042 OpenUrl CrossRef PubMed Cohen , J. D. , Javed , A. A. , Thoburn , C. , Wong , F. , Tie , J. , Gibbs , P. , Schmidt , C. M. , Yip-Schneider , M. T. , Allen , P. J. , Schattner , M. , Brand , R. E. , Singhi , A. D. , Petersen , G. M. , Hong , S.-M. , Kim , S. C. , Falconi , M. , Doglioni , C. , Weiss , M. J. , Ahuja , N. , … Lennon , A. M . ( 2017 ). Combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancers . Proceedings of the National Academy of Sciences , 114 ( 38 ), 10202 – 10207 . doi: 10.1073/pnas.1704961114 OpenUrl Abstract / FREE Full Text Connor , A. A. , Denroche , R. E. , Jang , G. H. , Lemire , M. , Zhang , A. , Chan-Seng-Yue , M. , Wilson , G. , Grant , R. C. , Merico , D. , Lungu , I. , Bartlett , J. M. S. , Chadwick , D. , Liang , S.-B. , Eagles , J. , Mbabaali , F. , Miller , J. K. , Krzyzanowski , P. , Armstrong , H. , Luo , X. , … Gallinger , S . ( 2019 ). Integration of Genomic and Transcriptional Features in Pancreatic Cancer Reveals Increased Cell Cycle Progression in Metastases . Cancer Cell , 35 ( 2 ), 267 – 282 .e7. doi: 10.1016/j.ccell.2018.12.010 OpenUrl CrossRef PubMed Conroy , T. , Desseigne , F. , Ychou , M. , Bouché , O. , Guimbaud , R. , Bécouarn , Y. , Adenis , A. , Raoul , J.-L. , Gourgou-Bourgade , S. , de la Fouchardière , C. , Bennouna , J. , Bachet , J.-B. , Khemissa-Akouz , F. , Péré-Vergé , D. , Delbaldo , C. , Assenat , E. , Chauffert , B. , Michel , P. , Montoto-Grillot , C. , & Ducreux , M . ( 2011 ). FOLFIRINOX versus Gemcitabine for Metastatic Pancreatic Cancer . New England Journal of Medicine , 364 ( 19 ), 1817 – 1825 . doi: 10.1056/NEJMoa1011923 OpenUrl CrossRef PubMed Web of Science Conroy , T. , Hammel , P. , Hebbar , M. , Ben Abdelghani , M. , Wei , A. C. , Raoul , J.-L. , Choné , L. , Francois , E. , Artru , P. , Biagi , J. J. , Lecomte , T. , Assenat , E. , Faroux , R. , Ychou , M. , Volet , J. , Sauvanet , A. , Breysacher , G. , Di Fiore , F. , Cripps , C. , … Bachet , J.-B . ( 2018 ). FOLFIRINOX or Gemcitabine as Adjuvant Therapy for Pancreatic Cancer . New England Journal of Medicine , 379 ( 25 ), 2395 – 2406 . doi: 10.1056/NEJMoa1809775 OpenUrl CrossRef PubMed Conroy , T. , Pfeiffer , P. , Vilgrain , V. , Lamarca , A. , Seufferlein , T. , O’Reilly , E. M. , Hackert , T. , Golan , T. , Prager , G. , Haustermans , K. , Vogel , A. , & Ducreux , M . ( 2023 ). Pancreatic cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up . Annals of Oncology , 34 ( 11 ), 987 – 1002 . doi: 10.1016/j.annonc.2023.08.009 OpenUrl CrossRef PubMed Croome , K. P. , Farnell , M. B. , Que , F. G. , Reid-Lombardo , Km ., Truty , M. J. , Nagorney , D. M. , & Kendrick , M. L . ( 2015 ). Pancreaticoduodenectomy with Major Vascular Resection: A Comparison of Laparoscopic Versus Open Approaches . Journal of Gastrointestinal Surgery , 19 ( 1 ), 189 – 194 . doi: 10.1007/s11605-014-2644-8 OpenUrl CrossRef PubMed Cui , L. , Nakano , K. , Obchoei , S. , Setoguchi , K. , Matsumoto , M. , Yamamoto , T. , Obika , S. , Shimada , K. , & Hiraoka , N . ( 2017 ). Small Nucleolar Noncoding RNA SNORA23, Up-Regulated in Human Pancreatic Ductal Adenocarcinoma, Regulates Expression of Spectrin Repeat-Containing Nuclear Envelope 2 to Promote Growth and Metastasis of Xenograft Tumors in Mice . Gastroenterology , 153 ( 1 ), 292 – 306 .e2. doi: 10.1053/j.gastro.2017.03.050 OpenUrl CrossRef PubMed Daoud , A. Z. , Mulholland , E. J. , Cole , G. , & McCarthy , H. O . ( 2019 ). MicroRNAs in Pancreatic Cancer: Biomarkers, prognostic, and therapeutic modulators . BMC Cancer , 19 ( 1 ), 1130 . doi: 10.1186/s12885-019-6284-y OpenUrl CrossRef PubMed Dardare , J. , Witz , A. , Merlin , J.-L. , Gilson , P. , & Harlé , A . ( 2020 ). SMAD4 and the TGFβ Pathway in Patients with Pancreatic Ductal Adenocarcinoma . International Journal of Molecular Sciences , 21 ( 10 ), 3534 . doi: 10.3390/ijms21103534 OpenUrl CrossRef PubMed de Geus , S. W. L. , Eskander , M. F. , Kasumova , G. G. , Ng , S. C. , Kent , T. S. , Mancias , J. D. , Callery , M. P. , Mahadevan , A. , & Tseng , J. F. ( 2017 ). Stereotactic body radiotherapy for unresected pancreatic cancer: A nationwide review . Cancer , 123 ( 21 ), 4158 – 4167 . doi: 10.1002/cncr.30856 OpenUrl CrossRef PubMed ↵ de Martel , C. , Georges , D. , Bray , F. , Ferlay , J. , & Clifford , G. M. ( 2020 ). Global burden of cancer attributable to infections in 2018: A worldwide incidence analysis . The Lancet Global Health , 8 ( 2 ), e180 – e190 . doi: 10.1016/S2214-109X(19)30488-7 OpenUrl CrossRef PubMed Dewani , D. , Karwade , P. , & Mahajan , K. S . ( 2023 ). Uterine Transplantation and Fertility Preservation: A Hopeful Horizon for Cancer Survivors . Cureus . doi: 10.7759/cureus.50178 OpenUrl CrossRef Ding , L. , Madamsetty , V. S. , Kiers , S. , Alekhina , O. , Ugolkov , A. , Dube , J. , Zhang , Y. , Zhang , J.-S. , Wang , E. , Dutta , S. K. , Schmitt , D. M. , Giles , F. J. , Kozikowski , A. P. , Mazar , A. P. , Mukhopadhyay , D. , & Billadeau , D. D . ( 2019 ). Glycogen Synthase Kinase-3 Inhibition Sensitizes Pancreatic Cancer Cells to Chemotherapy by Abrogating the TopBP1/ATR-Mediated DNA Damage Response . Clinical Cancer Research , 25 ( 21 ), 6452 – 6462 . doi: 10.1158/1078-0432.CCR-19-0799 OpenUrl Abstract / FREE Full Text Du , Y. , Song , W. , Chen , J. , Chen , H. , Xuan , Z. , Zhao , L. , Chen , J. , Jin , C. , Zhou , M. , Tuo , B. , Zhao , Y. , Zheng , S. , & Song , P . ( 2019 ). The potassium channel KCa3.1 promotes cell proliferation by activating SKP2 and metastasis through the EMT pathway in hepatocellular carcinoma . International Journal of Cancer , 145 ( 2 ), 503 – 516 . doi: 10.1002/ijc.32121 OpenUrl CrossRef PubMed Ebrahimi , S. , Hosseini , M. , Shahidsales , S. , Maftouh , M. , Ferns , G. A. , Ghayour-Mobarhan , M. , Hassanian , S. M. , & Avan , A . ( 2017 ). Targeting the Akt/PI3K Signaling Pathway as a Potential Therapeutic Strategy for the Treatment of Pancreatic Cancer . Current Medicinal Chemistry , 24 ( 13 ). doi: 10.2174/0929867324666170206142658 OpenUrl CrossRef PubMed Eibl , G. , & Rozengurt , E . ( 2019 ). KRAS, YAP, and obesity in pancreatic cancer: A signaling network with multiple loops . Seminars in Cancer Biology , 54 , 50 – 62 . doi: 10.1016/j.semcancer.2017.10.007 OpenUrl CrossRef PubMed Esfahani , S. A. , Heidari , P. , Kim , S. A. , Ogino , S. , & Mahmood , U . ( 2016 ). Optical Imaging of Mesenchymal Epithelial Transition Factor (MET) for Enhanced Detection and Characterization of Primary and Metastatic Hepatic Tumors . Theranostics , 6 ( 12 ), 2028 – 2038 . doi: 10.7150/thno.15718 OpenUrl CrossRef PubMed ↵ Faber , E. S. L. , & Sah , P . ( 2003 ). Calcium-Activated Potassium Channels: Multiple Contributions to Neuronal Function . The Neuroscientist , 9 ( 3 ), 181 – 194 . doi: 10.1177/1073858403009003011 OpenUrl CrossRef PubMed Web of Science Fang , C. , Guo , X. , Lv , X. , Yin , R. , Lv , X. , Wang , F. , Zhao , J. , Bai , Q. , Yao , X. , & Chen , Y . ( 2017 ). Dysbindin promotes progression of pancreatic ductal adenocarcinoma via direct activation of PI3K . Journal of Molecular Cell Biology , 9 ( 6 ), 504 – 515 . doi: 10.1093/jmcb/mjx043 OpenUrl CrossRef PubMed Feigin , M. E. , Garvin , T. , Bailey , P. , Waddell , N. , Chang , D. K. , Kelley , D. R. , Shuai , S. , Gallinger , S. , McPherson , J. D. , Grimmond , S. M. , Khurana , E. , Stein , L. D. , Biankin , A. V. , Schatz , M. C. , & Tuveson , D. A . ( 2017 ). Recurrent noncoding regulatory mutations in pancreatic ductal adenocarcinoma . Nature Genetics , 49 ( 6 ), 825 – 833 . doi: 10.1038/ng.3861 OpenUrl CrossRef ↵ Ferlay , J. , Ervik , M. , Lam , F. , Colombet , M. , Mery , L. , Piñeros , M. , Znaor , A. , Soerjomataram , I. , & Bray , F . ( 2020 ). Global cancer observatory: Cancer today . Lyon: International Agency for Research on Cancer , 20182020 . ↵ Ferlay , J. , Partensky , C. , & Bray , F . ( 2016 ). More deaths from pancreatic cancer than breast cancer in the EU by 2017 . Acta Oncologica , 55 ( 9–10 ), 1158 – 1160 . doi: 10.1080/0284186X.2016.1197419 OpenUrl CrossRef PubMed Fernández , M. A. , Rueda , C. , & Peddada , S. D . ( 2012 ). Identification of a core set of signature cell cycle genes whose relative order of time to peak expression is conserved across species . Nucleic Acids Research , 40 ( 7 ), 2823 – 2832 . doi: 10.1093/nar/gkr1077 OpenUrl CrossRef PubMed Web of Science ↵ Feske , S. , Wulff , H. , & Skolnik , E. Y . ( 2015 ). Ion Channels in Innate and Adaptive Immunity . Annual Review of Immunology , 33 ( 1 ), 291 – 353 . doi: 10.1146/annurev-immunol-032414-112212 OpenUrl CrossRef PubMed ↵ Gao , J. , Aksoy , B. A. , Dogrusoz , U. , Dresdner , G. , Gross , B. , Sumer , S. O. , Sun , Y. , Jacobsen , A. , Sinha , R. , Larsson , E. , Cerami , E. , Sander , C. , & Schultz , N . ( 2013 ). Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal . Science Signaling , 6 ( 269 ). doi: 10.1126/scisignal.2004088 OpenUrl Abstract / FREE Full Text ↵ Gao , J. , Mazor , T. , Ciftci , E. , Raman , P. , Lukasse , P. , Bahceci , I. , Sigaras , A. , Abeshouse , A. , Bruijn , I. de , Gross , B. , Kundra , R. , Lisman , A. , Ochoa , A. , Sheridan , R. , Su , J. , Sumer , S. O. , Sun , Y. , Wang , A. , Wang , J. , … Cerami , E. ( 2018 ). Abstract 923: The cBioPortal for Cancer Genomics: An intuitive open-source platform for exploration, analysis and visualization of cancer genomics data . Cancer Research , 78 (13_Supplement), 923–923. doi: 10.1158/1538-7445.AM2018-923 OpenUrl CrossRef Gao , X. , & Homayoonfal , M . ( 2023 ). Exploring the anti-cancer potential of Ganoderma lucidum polysaccharides (GLPs) and their versatile role in enhancing drug delivery systems: A multifaceted approach to combat cancer . Cancer Cell International , 23 ( 1 ), 324 . doi: 10.1186/s12935-023-03146-8 OpenUrl CrossRef PubMed ↵ George Chandy , K. , Wulff , H. , Beeton , C. , Pennington , M. , Gutman , G. A. , & Cahalan , M. D. . ( 2004 ). K+ channels as targets for specific immunomodulation . Trends in Pharmacological Sciences , 25 ( 5 ), 280 – 289 . doi: 10.1016/j.tips.2004.03.010 OpenUrl CrossRef PubMed Gherardi , E. , Birchmeier , W. , Birchmeier , C. , & Woude , G. V . ( 2012 ). Targeting MET in cancer: Rationale and progress . Nature Reviews Cancer , 12 ( 2 ), 89 – 103 . doi: 10.1038/nrc3205 OpenUrl CrossRef PubMed Web of Science Golan , T. , Hammel , P. , Reni , M. , Van Cutsem , E. , Macarulla , T. , Hall , M. J. , Park , J.-O. , Hochhauser , D. , Arnold , D. , Oh , D.-Y. , Reinacher-Schick , A. , Tortora , G. , Algül , H. , O’Reilly , E. M. , McGuinness , D. , Cui , K. Y. , Schlienger , K. , Locker , G. Y. , & Kindler , H. L . ( 2019 ). Maintenance Olaparib for Germline BRCA -Mutated Metastatic Pancreatic Cancer . New England Journal of Medicine , 381 ( 4 ), 317 – 327 . doi: 10.1056/NEJMoa1903387 OpenUrl CrossRef PubMed ↵ Goldman , M. , Craft , B. , Zhu , J. , & Haussler , D . ( 2017 ). Abstract 2584: The UCSC Xena system for cancer genomics data visualization and interpretation . Cancer Research , 77 (13_Supplement), 2584–2584. doi: 10.1158/1538-7445.AM2017-2584 OpenUrl CrossRef Grbovic-Huezo , O. , Pitter , K. L. , Lecomte , N. , Saglimbeni , J. , Askan , G. , Holm , M. , Melchor , J. P. , Chandwani , R. , Joshi , S. , Haglund , C. , Iacobuzio-Donahue , C. A. , Chiosis , G. , Tammela , T. , & Leach , S. D . ( 2020 ). Unbiased in vivo preclinical evaluation of anticancer drugs identifies effective therapy for the treatment of pancreatic adenocarcinoma . Proceedings of the National Academy of Sciences , 117 ( 48 ), 30670 – 30678 . doi: 10.1073/pnas.1920240117 OpenUrl Abstract / FREE Full Text Grössinger , E. M. , Kang , M. , Bouchareychas , L. , Sarin , R. , Haudenschild , D. R. , Borodinsky , L. N. , & Adamopoulos , I. E . ( 2018 ). Ca2+-Dependent Regulation of NFATc1 via KCa3.1 in Inflammatory Osteoclastogenesis . The Journal of Immunology , 200 ( 2 ), 749 – 757 . doi: 10.4049/jimmunol.1701170 OpenUrl Abstract / FREE Full Text Grünwald , B. , Harant , V. , Schaten , S. , Frühschütz , M. , Spallek , R. , Höchst , B. , Stutzer , K. , Berchtold , S. , Erkan , M. , Prokopchuk , O. , Martignoni , M. , Esposito , I. , Heikenwalder , M. , Gupta , A. , Siveke , J. , Saftig , P. , Knolle , P. , Wohlleber , D. , & Krüger , A . ( 2016 ). Pancreatic Premalignant Lesions Secrete Tissue Inhibitor of Metalloproteinases-1, Which Activates Hepatic Stellate Cells Via CD63 Signaling to Create a Premetastatic Niche in the Liver . Gastroenterology , 151 ( 5 ), 1011 – 1024 .e7. doi: 10.1053/j.gastro.2016.07.043 OpenUrl CrossRef PubMed Guo , X. , Zhou , Q. , Su , D. , Luo , Y. , Fu , Z. , Huang , L. , Li , Z. , Jiang , D. , Kong , Y. , Li , Z. , Chen , R. , & Chen , C . ( 2020 ). Circular RNA circBFAR promotes the progression of pancreatic ductal adenocarcinoma via the miR-34b-5p/MET/Akt axis . Molecular Cancer , 19 ( 1 ), 83 . doi: 10.1186/s12943-020-01196-4 OpenUrl CrossRef PubMed Guren , M. G . ( 2019 ). The global challenge of colorectal cancer . The Lancet Gastroenterology & Hepatology , 4 ( 12 ), 894 – 895 . doi: 10.1016/S2468-1253(19)30329-2 OpenUrl CrossRef PubMed Hegde , S. , Krisnawan , V. E. , Herzog , B. H. , Zuo , C. , Breden , M. A. , Knolhoff , B. L. , Hogg , G. D. , Tang , J. P. , Baer , J. M. , Mpoy , C. , Lee , K. B. , Alexander , K. A. , Rogers , B. E. , Murphy , K. M. , Hawkins , W. G. , Fields , R. C. , DeSelm , C. J. , Schwarz , J. K. , & DeNardo , D. G . ( 2020 ). Dendritic Cell Paucity Leads to Dysfunctional Immune Surveillance in Pancreatic Cancer . Cancer Cell , 37 ( 3 ), 289 – 307 .e9. doi: 10.1016/j.ccell.2020.02.008 OpenUrl CrossRef PubMed Heiler , S. , Wang , Z. , & Zöller , M . ( 2016 ). Pancreatic cancer stem cell markers and exosomes— The incentive push . World Journal of Gastroenterology , 22 ( 26 ), 5971 . doi: 10.3748/wjg.v22.i26.5971 OpenUrl CrossRef PubMed Hodi , F. S. , O’Day , S. J. , McDermott , D. F. , Weber , R. W. , Sosman , J. A. , Haanen , J. B. , Gonzalez , R. , Robert , C. , Schadendorf , D. , Hassel , J. C. , Akerley , W. , van den Eertwegh , A. J. M. , Lutzky , J. , Lorigan , P. , Vaubel , J. M. , Linette , G. P. , Hogg , D. , Ottensmeier , C. H. , Lebbé , C. , … Urba , W. J. ( 2010 ). Improved Survival with Ipilimumab in Patients with Metastatic Melanoma . New England Journal of Medicine , 363 ( 8 ), 711 – 723 . doi: 10.1056/NEJMoa1003466 OpenUrl CrossRef PubMed ↵ Hoffman , J. F. , Joiner , W. , Nehrke , K. , Potapova , O. , Foye , K. , & Wickrema , A . ( 2003 ). The hSK4 (KCNN4) isoform is the Ca 2 + -activated K + channel (Gardos channel) in human red blood cells . Proceedings of the National Academy of Sciences , 100 ( 12 ), 7366 – 7371 . doi: 10.1073/pnas.1232342100 OpenUrl Abstract / FREE Full Text Holohan , C. , Van Schaeybroeck , S. , Longley , D. B. , & Johnston , P. G. ( 2013 ). Cancer drug resistance: An evolving paradigm . Nature Reviews Cancer , 13 ( 10 ), 714 – 726 . doi: 10.1038/nrc3599 OpenUrl CrossRef PubMed Web of Science Hung , Y.-H. , Hsu , M.-C. , Chen , L.-T. , Hung , W.-C. , & Pan , M.-R . ( 2019 ). Alteration of Epigenetic Modifiers in Pancreatic Cancer and Its Clinical Implication . Journal of Clinical Medicine , 8 ( 6 ), 903 . doi: 10.3390/jcm8060903 OpenUrl CrossRef PubMed Igbinigie , E. , Guo , F. , Jiang , S.-W. , Kelley , C. , & Li , J . ( 2019 ). Dkk1 involvement and its potential as a biomarker in pancreatic ductal adenocarcinoma . Clinica Chimica Acta , 488 , 226 – 234 . doi: 10.1016/j.cca.2018.11.023 OpenUrl CrossRef ↵ Ilic , I. , & Ilic , M . ( 2022 ). International patterns in incidence and mortality trends of pancreatic cancer in the last three decades: A joinpoint regression analysis . World Journal of Gastroenterology , 28 ( 32 ), 4698 – 4715 . doi: 10.3748/wjg.v28.i32.4698 OpenUrl CrossRef PubMed ↵ Ilic , I. , & Ilic , M . ( 2024 ). Global Burden of Pancreatic Cancer Attributable to High Body-Mass Index in 204 Countries and Territories, 1990–2019 . Cancers , 16 ( 4 ), 719 . doi: 10.3390/cancers16040719 OpenUrl CrossRef PubMed ↵ Islami , F. , Goding Sauer , A. , Miller , K. D. , Siegel , R. L. , Fedewa , S. A. , Jacobs , E. J. , McCullough , M. L. , Patel , A. V. , Ma , J. , Soerjomataram , I. , Flanders , W. D. , Brawley , O. W. , Gapstur , S. M. , & Jemal , A. ( 2018 ). Proportion and number of cancer cases and deaths attributable to potentially modifiable risk factors in the United States . CA: A Cancer Journal for Clinicians , 68 ( 1 ), 31 – 54 . doi: 10.3322/caac.21440 OpenUrl CrossRef PubMed Israel Osejie Okoduwa , Bankole Ibrahim Ashiwaju , Jane Osareme Ogugua , Jeremiah Olawumi Arowoogun , Kehinde Feranmi Awonuga , & Evangel Chinyere Anyanwu . ( 2024 ). Reviewing the progress of cancer research in the USA . World Journal of Biology Pharmacy and Health Sciences , 17 ( 2 ), 068 – 079 . doi: 10.30574/wjbphs.2024.17.2.0046 OpenUrl CrossRef ↵ Jäger , H. , Dreker , T. , Buck , A. , Giehl , K. , Gress , T. , & Grissmer , S . ( 2004 ). Blockage of Intermediate-Conductance Ca 2+ -Activated K + Channels Inhibit Human Pancreatic Cancer Cell Growth in Vitro . Molecular Pharmacology , 65 ( 3 ), 630 – 638 . doi: 10.1124/mol.65.3.630 OpenUrl Abstract / FREE Full Text ↵ Jemal , A. , Siegel , R. , Ward , E. , Murray , T. , Xu , J. , Smigal , C. , & Thun , M. J . ( 2006 ). Cancer Statistics, 2006 . CA: A Cancer Journal for Clinicians , 56 ( 2 ), 106 – 130 . doi: 10.3322/canjclin.56.2.106 OpenUrl CrossRef PubMed Web of Science ↵ Jensen , B. , Hertz , M. , Christophersen , P. , & Madsen , L . ( 2002 ). The Ca 2+ -activated K + channel of intermediate conductance:a possible target for immune suppression . Expert Opinion on Therapeutic Targets , 6 ( 6 ), 623 – 636 . doi: 10.1517/14728222.6.6.623 OpenUrl CrossRef PubMed ↵ Jiao , X.-D. , He , X. , Qin , B.-D. , Liu , K. , Wu , Y. , Liu , J. , Hou , T. , & Zang , Y.-S . ( 2019 ). The prognostic value of tumor mutation burden in EGFR-mutant advanced lung adenocarcinoma, an analysis based on cBioPortal data base . Journal of Thoracic Disease , 11 ( 11 ), 4507 – 4515 . doi: 10.21037/jtd.2019.11.04 OpenUrl CrossRef PubMed ↵ Joiner , W. J. , Wang , L.-Y. , Tang , M. D. , & Kaczmarek , L. K . ( 1997 ). HSK4, a member of a novel subfamily of calcium-activated potassium channels . Proceedings of the National Academy of Sciences , 94 ( 20 ), 11013 – 11018 . doi: 10.1073/pnas.94.20.11013 OpenUrl Abstract / FREE Full Text Kamisawa , T. , Wood , L. D. , Itoi , T. , & Takaori , K . ( 2016 ). Pancreatic cancer . The Lancet , 388 ( 10039 ), 73 – 85 . doi: 10.1016/S0140-6736(16)00141-0 OpenUrl CrossRef PubMed Kang , H. , Kerloc’h , A. , Rotival , M. , Xu , X. , Zhang , Q. , D’Souza , Z. , Kim , M. , Scholz , J. C. , Ko , J.-H. , Srivastava , P. K. , Genzen , J. R. , Cui , W. , Aitman , T. J. , Game , L. , Melvin , J. E. , Hanidu , A. , Dimock , J. , Zheng , J. , Souza , D. , … Behmoaras , J . ( 2014 ). Kcnn4 Is a Regulator of Macrophage Multinucleation in Bone Homeostasis and Inflammatory Disease . Cell Reports , 8 ( 4 ), 1210 – 1224 . doi: 10.1016/j.celrep.2014.07.032 OpenUrl CrossRef PubMed Kantarjian , H. , Steensma , D. , Rius Sanjuan , J. , Elshaug , A. , & Light , D . ( 2014 ). High Cancer Drug Prices in the United States: Reasons and Proposed Solutions . Journal of Oncology Practice , 10 ( 4 ), e208 – e211 . doi: 10.1200/JOP.2013.001351 OpenUrl Abstract / FREE Full Text Karakas , Y. , Lacin , S. , & Yalcin , S . ( 2018 ). Recent advances in the management of pancreatic adenocarcinoma . Expert Review of Anticancer Therapy , 18 ( 1 ), 51 – 62 . doi: 10.1080/14737140.2018.1403319 OpenUrl CrossRef PubMed Kelderman , S. , Schumacher , T. N. M. , & Haanen , J. B. A. G . ( 2014 ). Acquired and intrinsic resistance in cancer immunotherapy . Molecular Oncology , 8 ( 6 ), 1132 – 1139 . doi: 10.1016/j.molonc.2014.07.011 OpenUrl CrossRef PubMed Khurana , N. , Dodhiawala , P. B. , Bulle , A. , & Lim , K.-H . ( 2020 ). Deciphering the Role of Innate Immune NF-ĸB Pathway in Pancreatic Cancer . Cancers , 12 ( 9 ), 2675 . doi: 10.3390/cancers12092675 OpenUrl CrossRef PubMed Kirkegård , J. , Aahlin , E. K. , Al-Saiddi , M. , Bratlie , S. O. , Coolsen , M. , de Haas , R. J. , den Dulk , M. , Fristrup , C. , Harrison , E. M. , Mortensen , M. B. , Nijkamp , M. W. , Persson , J. , Søreide , J. A. , Wigmore , S. J. , Wik , T. , & Mortensen , F. V . ( 2019 ). Multicentre study of multidisciplinary team assessment of pancreatic cancer resectability and treatment allocation . British Journal of Surgery , 106 ( 6 ), 756 – 764 . doi: 10.1002/bjs.11093 OpenUrl CrossRef PubMed Kleeff , J. , Korc , M. , Apte , M. , La Vecchia , C. , Johnson , C. D. , Biankin , A. V. , Neale , R. E. , Tempero , M. , Tuveson , D. A. , Hruban , R. H. , & Neoptolemos , J. P. ( 2016 ). Pancreatic cancer . Nature Reviews Disease Primers , 2 ( 1 ), 16022 . doi: 10.1038/nrdp.2016.22 OpenUrl CrossRef PubMed Kong , Y. , Li , Y. , Luo , Y. , Zhu , J. , Zheng , H. , Gao , B. , Guo , X. , Li , Z. , Chen , R. , & Chen , C . ( 2020 ). CircNFIB1 inhibits lymphangiogenesis and lymphatic metastasis via the miR-486-5p/PIK3R1/VEGF-C axis in pancreatic cancer . Molecular Cancer , 19 ( 1 ), 82 . doi: 10.1186/s12943-020-01205-6 OpenUrl CrossRef PubMed Kromrey , M.-L. , Bülow , R. , Hübner , J. , Paperlein , C. , Lerch , M. M. , Ittermann , T. , Völzke , H. , Mayerle , J. , & Kühn , J.-P . ( 2018 ). Prospective study on the incidence, prevalence and 5-year pancreatic-related mortality of pancreatic cysts in a population-based study . Gut , 67 ( 1 ), 138 – 145 . doi: 10.1136/gutjnl-2016-313127 OpenUrl Abstract / FREE Full Text Lai , W. , Liu , L. , Zeng , Y. , Wu , H. , Xu , H. , Chen , S. , & Chu , Z . ( 2013 ). KCNN4 Channels participate in the EMT induced by PRL-3 in colorectal cancer . Medical Oncology , 30 ( 2 ), 566 . doi: 10.1007/s12032-013-0566-z OpenUrl CrossRef PubMed Lallet-Daher , H. , Roudbaraki , M. , Bavencoffe , A. , Mariot , P. , Gackière , F. , Bidaux , G. , Urbain , R. , Gosset , P. , Delcourt , P. , Fleurisse , L. , Slomianny , C. , Dewailly , E. , Mauroy , B. , Bonnal , J. L. , Skryma , R. , & Prevarskaya , N . ( 2009 ). Intermediate-conductance Ca2+-activated K+ channels (IKCa1) regulate human prostate cancer cell proliferation through a close control of calcium entry . Oncogene , 28 ( 15 ), 1792 – 1806 . doi: 10.1038/onc.2009.25 OpenUrl CrossRef PubMed Web of Science ↵ Lambert , A. W. , Pattabiraman , D. R. , & Weinberg , R. A . ( 2017 ). Emerging Biological Principles of Metastasis . Cell , 168 ( 4 ), 670 – 691 . doi: 10.1016/j.cell.2016.11.037 OpenUrl CrossRef PubMed Lee , J. , Park , S. S. , Lee , Y. K. , Norton , J. A. , & Jeffrey , S. S . ( 2019 ). Liquid biopsy in pancreatic ductal adenocarcinoma: Current status of circulating tumor cells and circulating tumor DNA . Molecular Oncology , 13 ( 8 ), 1623 – 1650 . doi: 10.1002/1878-0261.12537 OpenUrl CrossRef PubMed Li , D . ( 2012 ). Diabetes and pancreatic cancer . Molecular Carcinogenesis , 51 ( 1 ), 64 – 74 . doi: 10.1002/mc.20771 OpenUrl CrossRef PubMed Li , N. , Li , L. , & Chen , Y . ( 2018 ). The Identification of Core Gene Expression Signature in Hepatocellular Carcinoma . Oxidative Medicine and Cellular Longevity , 2018 ( 1 ), 3478305 . doi: 10.1155/2018/3478305 OpenUrl CrossRef Li , Y. , Zhu , Y. , Dai , G. , Wu , D. , Gao , Z. , Zhang , L. , Fan , Y. , & Department of Oncology, The Second Affiliated Hospital of Jiaxing University, Jiaxing 314000, China. (2020). Screening and validating the core biomarkers in patients with pancreatic ductal adenocarcinoma . Mathematical Biosciences and Engineering , 17 ( 1 ), 910 – 927 . doi: 10.3934/mbe.2020048 OpenUrl CrossRef Lin , P. , Li , J. , Ye , F. , Fu , W. , Hu , X. , Shao , Z. , & Song , C. (n.d.). KCNN4 induces multiple chemoresistance in breast cancer by regulating BCL2A . Ling , J. , & Chiao , P. J . ( 2019 ). Two Birds with One Stone: Therapeutic Targeting of IL1α Signaling Pathways in Pancreatic Ductal Adenocarcinoma and the Cancer-Associated Fibroblasts . Cancer Discovery , 9 ( 2 ), 173 – 175 . doi: 10.1158/2159-8290.CD-18-1460 OpenUrl Abstract / FREE Full Text Liu , H. , Deng , H. , Zhao , Y. , Li , C. , & Liang , Y . ( 2018 ). LncRNA XIST/miR-34a axis modulates the cell proliferation and tumor growth of thyroid cancer through MET-PI3K-AKT signaling . Journal of Experimental & Clinical Cancer Research , 37 ( 1 ), 279 . doi: 10.1186/s13046-018-0950-9 OpenUrl CrossRef PubMed Luna , J. , Boni , J. , Cuatrecasas , M. , Bofill-De Ros , X. , Núñez-Manchón , E. , Gironella , M. , Vaquero , E. C. , Arbones , M. L. , de la Luna , S. , & Fillat , C. ( 2019 ). DYRK1A modulates c-MET in pancreatic ductal adenocarcinoma to drive tumour growth . Gut , 68 ( 8 ), 1465 – 1476 . doi: 10.1136/gutjnl-2018-316128 OpenUrl Abstract / FREE Full Text Maisonneuve , P . ( 2019 ). Epidemiology and burden of pancreatic cancer . La Presse Médicale , 48 ( 3 ), e113 – e123 . doi: 10.1016/j.lpm.2019.02.030 OpenUrl CrossRef Martinez-Bosch , N. , Vinaixa , J. , & Navarro , P . ( 2018 ). Immune Evasion in Pancreatic Cancer: From Mechanisms to Therapy . Cancers , 10 ( 1 ), 6 . doi: 10.3390/cancers10010006 OpenUrl CrossRef PubMed Martini , V. , Timme-Bronsert , S. , Fichtner-Feigl , S. , Hoeppner , J. , & Kulemann , B . ( 2019 ). Circulating Tumor Cells in Pancreatic Cancer: Current Perspectives . Cancers , 11 ( 11 ), 1659 . doi: 10.3390/cancers11111659 OpenUrl CrossRef Mashouri , L. , Yousefi , H. , Aref , A. R. , Ahadi , A. mohammad, Molaei , F. , & Alahari , S. K. ( 2019 ). Exosomes: Composition, biogenesis, and mechanisms in cancer metastasis and drug resistance . Molecular Cancer , 18 ( 1 ), 75 . doi: 10.1186/s12943-019-0991-5 OpenUrl CrossRef PubMed McGuigan , A. , Kelly , P. , Turkington , R. C. , Jones , C. , Coleman , H. G. , & McCain , R. S . ( 2018 ). Pancreatic cancer: A review of clinical diagnosis, epidemiology, treatment and outcomes . World Journal of Gastroenterology , 24 ( 43 ), 4846 – 4861 . doi: 10.3748/wjg.v24.i43.4846 OpenUrl CrossRef PubMed Michot , J. M. , Bigenwald , C. , Champiat , S. , Collins , M. , Carbonnel , F. , Postel-Vinay , S. , Berdelou , A. , Varga , A. , Bahleda , R. , Hollebecque , A. , Massard , C. , Fuerea , A. , Ribrag , V. , Gazzah , A. , Armand , J. P. , Amellal , N. , Angevin , E. , Noel , N. , Boutros , C. , … Lambotte , O . ( 2016 ). Immune-related adverse events with immune checkpoint blockade: A comprehensive review . European Journal of Cancer , 54 , 139 – 148 . doi: 10.1016/j.ejca.2015.11.016 OpenUrl CrossRef PubMed Miller , K. D. , Fidler-Benaoudia , M. , Keegan , T. H. , Hipp , H. S. , Jemal , A. , & Siegel , R. L . ( 2020 ). Cancer statistics for adolescents and young adults, 2020 . CA: A Cancer Journal for Clinicians , 70 ( 6 ), 443 – 459 . doi: 10.3322/caac.21637 OpenUrl CrossRef PubMed Mizrahi , J. D. , Surana , R. , Valle , J. W. , & Shroff , R. T . ( 2020 ). Pancreatic cancer . The Lancet , 395 ( 10242 ), 2008 – 2020 . doi: 10.1016/S0140-6736(20)30974-0 OpenUrl CrossRef PubMed ↵ Mizuno , H. , Kitada , K. , Nakai , K. , & Sarai , A . ( 2009 ). PrognoScan: A new database for meta-analysis of the prognostic value of genes . BMC Medical Genomics , 2 ( 1 ), 18 . doi: 10.1186/1755-8794-2-18 OpenUrl CrossRef PubMed Morris , J. P. , Cano , D. A. , Sekine , S. , Wang , S. C. , & Hebrok , M . ( 2010 ). β-catenin blocks Kras-dependent reprogramming of acini into pancreatic cancer precursor lesions in mice . Journal of Clinical Investigation , 120 ( 2 ), 508 – 520 . doi: 10.1172/JCI40045 OpenUrl CrossRef PubMed Web of Science Murphy , K. M. , Brune , K. A. , Griffin , C. , Sollenberger , J. E. , Petersen , G. M. , Bansal , R. , Hruban , R. H. , & Kern , S. E. (n.d.). Evaluation of Candidate Genes MAP2K4, MADH4, ACVR1B, and BRCA2 in Familial Pancreatic Cancer: Deleterious BRCA2 Mutations in 17%. Nagrath , S. , Jack , R. M. , Sahai , V. , & Simeone , D. M . ( 2016 ). Opportunities and Challenges for Pancreatic Circulating Tumor Cells . Gastroenterology , 151 ( 3 ), 412 – 426 . doi: 10.1053/j.gastro.2016.05.052 OpenUrl CrossRef PubMed ↵ Nagy , Á. , Lánczky , A. , Menyhárt , O. , & Győrffy , B . ( 2018 ). Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets . Scientific Reports , 8 ( 1 ), 9227 . doi: 10.1038/s41598-018-27521-y OpenUrl CrossRef PubMed Nakamoto , M. , & Hisaoka , M . ( 2016 ). Clinicopathological Implications of Wingless/int1 (WNT) Signaling Pathway in Pancreatic Ductal Adenocarcinoma . Journal of UOEH , 38 ( 1 ), 1 – 8 . doi: 10.7888/juoeh.38.1 OpenUrl CrossRef PubMed Napoli , C. , Sperandio , N. , Lawlor , R. T. , Scarpa , A. , Molinari , H. , & Assfalg , M . ( 2012 ). Urine Metabolic Signature of Pancreatic Ductal Adenocarcinoma by 1 H Nuclear Magnetic Resonance: Identification, Mapping, and Evolution . Journal of Proteome Research , 11 ( 2 ), 1274 – 1283 . doi: 10.1021/pr200960u OpenUrl CrossRef PubMed Necchi , A. , Raggi , D. , Gallina , A. , Madison , R. , Colecchia , M. , Lucianò , R. , Montironi , R. , Giannatempo , P. , Farè , E. , Pederzoli , F. , Bandini , M. , Bianchi , M. , Colombo , R. , Gandaglia , G. , Fossati , N. , Marandino , L. , Capitanio , U. , Dehò , F. , Ali , S. M. , … Montorsi , F . ( 2020 ). Updated Results of PURE-01 with Preliminary Activity of Neoadjuvant Pembrolizumab in Patients with Muscle-invasive Bladder Carcinoma with Variant Histologies . European Urology , 77 ( 4 ), 439 – 446 . doi: 10.1016/j.eururo.2019.10.026 OpenUrl CrossRef PubMed Nelson , P. T. , Baldwin , D. A. , Scearce , L. M. , Oberholtzer , J. C. , Tobias , J. W. , & Mourelatos , Z . ( 2004 ). Microarray-based, high-throughput gene expression profiling of microRNAs . Nature Methods , 1 ( 2 ), 155 – 161 . doi: 10.1038/nmeth717 OpenUrl CrossRef PubMed Web of Science Noë , M. , Rezaee , N. , Asrani , K. , Skaro , M. , Groot , V. P. , Wu , P.-H. , Olson , M. T. , Hong , S.-M. , Kim , S. J. , Weiss , M. J. , Wolfgang , C. L. , Makary , M. A. , He , J. , Cameron , J. L. , Wirtz , D. , Roberts , N. J. , Offerhaus , G. J. A. , Brosens , L. A. A. , Wood , L. D. , & Hruban , R. H . ( 2018 ). Immunolabeling of Cleared Human Pancreata Provides Insights into Three-Dimensional Pancreatic Anatomy and Pathology . The American Journal of Pathology , 188 ( 7 ), 1530 – 1535 . doi: 10.1016/j.ajpath.2018.04.002 OpenUrl CrossRef PubMed ↵ Ohya , S. , & Kito , H . ( 2018 ). Ca 2+ -Activated K + Channel K Ca 3.1 as a Therapeutic Target for Immune Disorders . Biological and Pharmaceutical Bulletin , 41 ( 8 ), 1158 – 1163 . doi: 10.1248/bpb.b18-00078 OpenUrl CrossRef Sarkar B , Islam SS , Zohora US , Ullah MA . Virus like particles-A recent advancement in vaccine development . 미생물학회지 . 2019 Dec; 55 ( 4 ): 327 – 43 . DOI: 10.7845/kjm.2019.9089 OpenUrl CrossRef Pekarek , L. , Fraile-Μartinez , O. , Garcia-Montero , C. , Alvarez-Mon , M. , Acero , J. , Ruiz-Llorente , L. , García-Honduvilla , N. , Albillos , A. , Buján , J. , Alvarez-Mon , M. , Guijarro , L. , & Ortega , M. ( 2021 ). Towards an updated view on the clinical management of pancreatic adenocarcinoma: Current and future perspectives (Review) . Oncology Letters , 22 ( 5 ), 809 . doi: 10.3892/ol.2021.13070 OpenUrl CrossRef PubMed ↵ Pontén , F. , Jirström , K. , & Uhlen , M . ( 2008 ). The Human Protein Atlas—A tool for pathology . The Journal of Pathology , 216 ( 4 ), 387 – 393 . doi: 10.1002/path.2440 OpenUrl CrossRef PubMed Web of Science Prabhu , L. , Mundade , R. , Korc , M. , Loehrer , P. J. , & Lu , T . ( 2014 ). Critical role of NF-κB in pancreatic cancer . Oncotarget , 5 ( 22 ), 10969 – 10975 . doi: 10.18632/oncotarget.2624 OpenUrl CrossRef PubMed Previdi , M. C. , Carotenuto , P. , Zito , D. , Pandolfo , R. , & Braconi , C . ( 2017 ). Noncoding Rnas as Novel Biomarkers in Pancreatic Cancer: What do we Know? Future Oncology , 13 ( 5 ), 443 – 453 . doi: 10.2217/fon-2016-0253 OpenUrl CrossRef PubMed Pylayeva-Gupta , Y. , Grabocka , E. , & Bar-Sagi , D . ( 2011 ). RAS oncogenes: Weaving a tumorigenic web . Nature Reviews Cancer , 11 ( 11 ), 761 – 774 . doi: 10.1038/nrc3106 OpenUrl CrossRef PubMed Web of Science Qian , C. , Wan , L. , & Wu , Y . ( 2023 ). Analysis of the results of high-intensity focused ultrasound for patients with advanced pancreatic cancer . International Journal of Hyperthermia , 40 ( 1 ), 2250586 . doi: 10.1080/02656736.2023.2250586 OpenUrl CrossRef PubMed Moin AT , Sarkar B , Ullah MA , Araf Y , Ahmed N , Rudra B . In silico assessment of EpCAM transcriptional expression and determination of the prognostic biomarker for human lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) . Biochemistry and Biophysics Reports . 2021 Sep 1; 27 : 101074 . DOI: 10.1016/j.bbrep.2021.101074 OpenUrl CrossRef ↵ Rahib , L. , Smith , B. D. , Aizenberg , R. , Rosenzweig , A. B. , Fleshman , J. M. , & Matrisian , L. M . ( 2014 ). Projecting Cancer Incidence and Deaths to 2030: The Unexpected Burden of Thyroid, Liver, and Pancreas Cancers in the United States . Cancer Research , 74 ( 11 ), 2913 – 2921 . doi: 10.1158/0008-5472.CAN-14-0155 OpenUrl Abstract / FREE Full Text Rai , V. , Gupta , Y. , Srivastava , S. P. , Shukla , A. , Bano , N. , & Khan , S . ( 2024 ). Targeted Therapies in Cancer Treatment: Unveiling the Latest Breakthroughs and Promising Approaches . Journal for Research in Applied Sciences and Biotechnology , 2 ( 6 ), 175 – 183 . doi: 10.55544/jrasb.2.6.26 OpenUrl CrossRef Ram Makena , M. , Gatla , H. , Verlekar , D. , Sukhavasi , S ., K . Pandey , M., & C. Pramanik , K. ( 2019 ). Wnt/β-Catenin Signaling: The Culprit in Pancreatic Carcinogenesis and Therapeutic Resistance . International Journal of Molecular Sciences , 20 ( 17 ), 4242 . doi: 10.3390/ijms20174242 OpenUrl CrossRef PubMed Raphael , B. J. , Hruban , R. H. , Aguirre , A. J. , Moffitt , R. A. , Yeh , J. J. , Stewart , C. , Robertson , A. G. , Cherniack , A. D. , Gupta , M. , Getz , G. , Gabriel , S. B. , Meyerson , M. , Cibulskis , C. , Fei , S. S. , Hinoue , T. , Shen , H. , Laird , P. W. , Ling , S. , Lu , Y. , … Zenklusen , J. C . ( 2017 ). Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma . Cancer Cell , 32 ( 2 ), 185 – 203 .e13. doi: 10.1016/j.ccell.2017.07.007 OpenUrl CrossRef PubMed Ullah MA , Islam NN , Sarkar B , Araf Y , Zohora US , Rahman MS . Bioinformatics analysis on the prognostic significance of SOX9 gene and its transcriptional product in colorectal cancer . Human Gene . 2022 Sep 1; 33 : 201043 . DOI: 10.1016/j.humgen.2022.201043 OpenUrl CrossRef Rehman , M. , Khaled , A. , & Noel , M . ( 2022 ). Cytotoxic Chemotherapy in Advanced Pancreatic Cancer . Hematology/Oncology Clinics of North America , 36 ( 5 ), 1011 – 1018 . doi: 10.1016/j.hoc.2022.07.006 OpenUrl CrossRef PubMed Ren , X. , Chen , C. , Luo , Y. , Liu , M. , Li , Y. , Zheng , S. , Ye , H. , Fu , Z. , Li , M. , Li , Z. , & Chen , R . ( 2020 ). LncRNA-PLACT1 sustains activation of NF-κB pathway through a positive feedback loop with IκBα/E2F1 axis in pancreatic cancer . Molecular Cancer , 19 ( 1 ), 35 . doi: 10.1186/s12943-020-01153-1 OpenUrl CrossRef PubMed Riva , F. , Dronov , O. I. , Khomenko , D. I. , Huguet , F. , Louvet , C. , Mariani , P. , Stern , M.-H. , Lantz , O. , Proudhon , C. , Pierga , J.-Y. , & Bidard , F.-C . ( 2016 ). Clinical applications of circulating tumor DNA and circulating tumor cells in pancreatic cancer . Molecular Oncology , 10 ( 3 ), 481 – 493 . doi: 10.1016/j.molonc.2016.01.006 OpenUrl CrossRef PubMed Rombouts , S. J. E. , Vogel , J. A. , van Santvoort , H. C. , van Lienden , K. P. , van Hillegersberg , R. , Busch , O. R. C. , Besselink , M. G. H. , & Molenaar , I. Q. ( 2015 ). Systematic review of innovative ablative therapies for the treatment of locally advanced pancreatic cancer . British Journal of Surgery , 102 ( 3 ), 182 – 193 . doi: 10.1002/bjs.9716 OpenUrl CrossRef PubMed Sawyers , C . ( 2004 ). Targeted cancer therapy . Nature , 432 ( 7015 ), 294 – 297 . doi: 10.1038/nature03095 OpenUrl CrossRef PubMed Web of Science Shi , Y. , Gao , W. , Lytle , N. K. , Huang , P. , Yuan , X. , Dann , A. M. , Ridinger-Saison , M. , DelGiorno , K. E. , Antal , C. E. , Liang , G. , Atkins , A. R. , Erikson , G. , Sun , H. , Meisenhelder , J. , Terenziani , E. , Woo , G. , Fang , L. , Santisakultarm , T. P. , Manor , U. , … Hunter , T . ( 2019 ). Targeting LIF-mediated paracrine interaction for pancreatic cancer therapy and monitoring . Nature , 569 ( 7754 ), 131 – 135 . doi: 10.1038/s41586-019-1130-6 OpenUrl CrossRef PubMed Siegel , R. L. , Miller , K. D. , Fuchs , H. E. , & Jemal , A . ( 2022 ). Cancer statistics, 2022 . CA : A Cancer Journal for Clinicians , 72 (1), 7–33. doi: 10.3322/caac.21708 OpenUrl CrossRef PubMed ↵ Siegel , R. L. , Miller , K. D. , & Jemal , A. ( 2018 ). Cancer statistics, 2018 . CA: A Cancer Journal for Clinicians , 68 ( 1 ), 7 – 30 . doi: 10.3322/caac.21442 OpenUrl CrossRef PubMed Siegel , R. L. , Miller , K. D. , & Jemal , A. ( 2019 ). Cancer statistics, 2019 . CA: A Cancer Journal for Clinicians , 69 ( 1 ), 7 – 34 . doi: 10.3322/caac.21551 OpenUrl CrossRef PubMed Siegel , R. L. , Miller , K. D. , & Jemal , A. ( 2020 ). Cancer statistics, 2020 . CA: A Cancer Journal for Clinicians , 70 ( 1 ), 7 – 30 . doi: 10.3322/caac.21590 OpenUrl CrossRef PubMed Simms , L. A. , Doecke , J. D. , Roberts , R. L. , Fowler , E. V. , Zhao , Z. Z. , McGuckin , M. A. , Huang , N. , Hayward , N. K. , Webb , P. M. , Whiteman , D. C. , Cavanaugh , J. A. , McCallum , R. , Florin , T. H. , Barclay , M. L. , Gearry , R. B. , Merriman , T. R. , Montgomery , G. W. , & Radford-Smith , G. L . ( 2010 ). KCNN4 Gene Variant Is Associated With Ileal Crohn’s Disease in the Australian and New Zealand Population . American Journal of Gastroenterology , 105 ( 10 ), 2209 – 2217 . doi: 10.1038/ajg.2010.161 OpenUrl CrossRef PubMed Singh , K. , Pruski , M. , Bland , R. , Younes , M. , Guha , S. , Thosani , N. , Maitra , A. , Cash , B. D. , McAllister , F. , Logsdon , C. D. , Chang , J. T. , & Bailey-Lundberg , J. M . ( 2021 ). Kras mutation rate precisely orchestrates ductal derived pancreatic intraepithelial neoplasia and pancreatic cancer . Laboratory Investigation , 101 ( 2 ), 177 – 192 . doi: 10.1038/s41374-020-00490-5 OpenUrl CrossRef PubMed Song , M. , Bode , A. M. , Dong , Z. , & Lee , M.-H . ( 2019 ). AKT as a Therapeutic Target for Cancer . Cancer Research , 79 ( 6 ), 1019 – 1031 . doi: 10.1158/0008-5472.CAN-18-2738 OpenUrl Abstract / FREE Full Text Song , Y. , Tang , M.-Y. , Chen , W. , Wang , Z. , & Wang , S.-L . ( 2020 ). High JAK2 Protein Expression Predicts a Poor Prognosis in Patients with Resectable Pancreatic Ductal Adenocarcinoma . Disease Markers , 2020 , 1 – 8 . doi: 10.1155/2020/7656031 OpenUrl CrossRef Springfeld , C. , Ferrone , C. R. , Katz , M. H. G. , Philip , P. A. , Hong , T. S. , Hackert , T. , Büchler , M. W. , & Neoptolemos , J . ( 2023 ). Neoadjuvant therapy for pancreatic cancer . Nature Reviews Clinical Oncology , 20 ( 5 ), 318 – 337 . doi: 10.1038/s41571-023-00746-1 OpenUrl CrossRef PubMed Springfeld , C. , Jäger , D. , Büchler , M. W. , Strobel , O. , Hackert , T. , Palmer , D. H. , & Neoptolemos , J. P . ( 2019 ). Chemotherapy for pancreatic cancer . La Presse Médicale , 48 ( 3 ), e159 – e174 . doi: 10.1016/j.lpm.2019.02.025 OpenUrl CrossRef PubMed Stratton , M. R . ( 2011 ). Exploring the Genomes of Cancer Cells: Progress and Promise . Science , 331 ( 6024 ), 1553 – 1558 . doi: 10.1126/science.1204040 OpenUrl Abstract / FREE Full Text Sung , H. , Ferlay , J. , Siegel , R. L. , Laversanne , M. , Soerjomataram , I. , Jemal , A. , & Bray , F . ( 2021 ). Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries . CA: A Cancer Journal for Clinicians , 71 ( 3 ), 209 – 249 . doi: 10.3322/caac.21660 OpenUrl CrossRef PubMed Tago , K. , Funakoshi-Tago , M. , Ohta , S. , Kawata , H. , Saitoh , H. , Horie , H. , Aoki-Ohmura , C. , Yamauchi , J. , Tanaka , A. , Matsugi , J. , & Yanagisawa , K. ( 2019 ). Oncogenic Ras mutant causes the hyperactivation of NF-κB via acceleration of its transcriptional activation . Molecular Oncology , 13 ( 11 ), 2493 – 2510 . doi: 10.1002/1878-0261.12580 OpenUrl CrossRef PubMed Ullah MA , Sarkar B , Akter F . Prediction of biomarker signatures and therapeutic agents from blood sample against Pancreatic Ductal Adenocarcinoma (PDAC): A network-based study . Informatics in Medicine Unlocked . 2020 Jan 1; 19 : 100346 . DOI: 10.1016/j.imu.2020.100346 OpenUrl CrossRef ↵ Tang , Z. , Li , C. , Kang , B. , Gao , G. , Li , C. , & Zhang , Z . ( 2017 ). GEPIA: A web server for cancer and normal gene expression profiling and interactive analyses . Nucleic Acids Research , 45 ( W1 ), W98 – W102 . doi: 10.1093/nar/gkx247 OpenUrl CrossRef PubMed Tiwari , A. , Tashiro , K. , Dixit , A. , Soni , A. , Vogel , K. , Hall , B. , Shafqat , I. , Slaughter , J. , Param , N. , Le , A. , Saunders , E. , Paithane , U. , Garcia , G. , Campos , A. R. , Zettervall , J. , Carlson , M. , Starr , T. K. , Marahrens , Y. , Deshpande , A. J. , … Bagchi , A . ( 2020 ). Loss of HIF1A From Pancreatic Cancer Cells Increases Expression of PPP1R1B and Degradation of p53 to Promote Invasion and Metastasis . Gastroenterology , 159 ( 5 ), 1882 – 1897 .e5. doi: 10.1053/j.gastro.2020.07.046 OpenUrl CrossRef PubMed ↵ Torre , L. A. , Siegel , R. L. , Ward , E. M. , & Jemal , A . ( 2016 ). Global Cancer Incidence and Mortality Rates and Trends—An Update . Cancer Epidemiology, Biomarkers & Prevention , 25 ( 1 ), 16 – 27 . doi: 10.1158/1055-9965.EPI-15-0578 OpenUrl Abstract / FREE Full Text Turner , K. L. , Honasoge , A. , Robert , S. M. , McFerrin , M. M. , & Sontheimer , H . ( 2014 ). A proinvasive role for the Ca 2+ -activated K + channel KCa3.1 in malignant glioma . Glia , 62 ( 6 ), 971 – 981 . doi: 10.1002/glia.22655 OpenUrl CrossRef PubMed ↵ Upadhyay , A . ( 2021 ). Cancer: An unknown territory; rethinking before going ahead . Genes & Diseases , 8 ( 5 ), 655 – 661 . doi: 10.1016/j.gendis.2020.09.002 OpenUrl CrossRef PubMed Ushio , J. , Kanno , A. , Ikeda , E. , Ando , K. , Nagai , H. , Miwata , T. , Kawasaki , Y. , Tada , Y. , Yokoyama , K. , Numao , N. , Tamada , K. , Lefor , A. K. , & Yamamoto , H . ( 2021 ). Pancreatic Ductal Adenocarcinoma: Epidemiology and Risk Factors . Diagnostics , 11 ( 3 ), 562 . doi: 10.3390/diagnostics11030562 OpenUrl CrossRef PubMed van Rijssen , L. B. , Rombouts , S. J. E. , Walma , M. S. , Vogel , J. A. , Tol , J. A. , Molenaar , I. Q. , van Eijck , C. H. J. , Verheij , J. , van de Vijver , M. J. , Busch , O. R. C. , & Besselink , M. G. H. ( 2016 ). Recent Advances in Pancreatic Cancer Surgery of Relevance to the Practicing Pathologist . Surgical Pathology Clinics , 9 ( 4 ), 539 – 545 . doi: 10.1016/j.path.2016.05.002 OpenUrl CrossRef PubMed ↵ Vander Heiden , M. G. , & DeBerardinis , R. J . ( 2017 ). Understanding the Intersections between Metabolism and Cancer Biology . Cell , 168 ( 4 ), 657 – 669 . doi: 10.1016/j.cell.2016.12.039 OpenUrl CrossRef PubMed Vincent , A. , Herman , J. , Schulick , R. , Hruban , R. H. , & Goggins , M . ( 2011 ). Pancreatic cancer . The Lancet , 378 ( 9791 ), 607 – 620 . doi: 10.1016/S0140-6736(10)62307-0 OpenUrl CrossRef PubMed Web of Science Von Hoff , D. D. , Ervin , T. , Arena , F. P. , Chiorean , E. G. , Infante , J. , Moore , M. , Seay , T. , Tjulandin , S. A. , Ma , W. W. , Saleh , M. N. , Harris , M. , Reni , M. , Dowden , S. , Laheru , D. , Bahary , N. , Ramanathan , R. K. , Tabernero , J. , Hidalgo , M. , Goldstein , D. , … Renschler , M. F . ( 2013 ). Increased Survival in Pancreatic Cancer with nab-Paclitaxel plus Gemcitabine . New England Journal of Medicine , 369 ( 18 ), 1691 – 1703 . doi: 10.1056/NEJMoa1304369 OpenUrl CrossRef PubMed Web of Science Wang , S. , Zheng , Y. , Yang , F. , Zhu , L. , Zhu , X.-Q. , Wang , Z.-F. , Wu , X.-L. , Zhou , C.-H. , Yan , J.-Y. , Hu , B.-Y. , Kong , B. , Fu , D.-L. , Bruns , C. , Zhao , Y. , Qin , L.-X. , & Dong , Q.-Z . ( 2021 ). The molecular biology of pancreatic adenocarcinoma: Translational challenges and clinical perspectives . Signal Transduction and Targeted Therapy , 6 ( 1 ), 249 . doi: 10.1038/s41392-021-00659-4 OpenUrl CrossRef PubMed Wang , Z. H. , Shen , B. , Yao , H. L. , Jia , Y. C. , Ren , J. , Feng , Y. J. , & Wang , Y. Z . ( 2007 ). Blockage of intermediate-conductance-Ca2+-activated K+ channels inhibits progression of human endometrial cancer . Oncogene , 26 ( 35 ), 5107 – 5114 . doi: 10.1038/sj.onc.1210308 OpenUrl CrossRef PubMed Web of Science Wang , Z. , Qin , J. , Zhao , J. , Li , J. , Li , D. , Popp , M. , Popp , F. , Alakus , H. , Kong , B. , Dong , Q. , Nelson , P. J. , Zhao , Y. , & Bruns , C. J . ( 2020 ). Inflammatory IFIT3 renders chemotherapy resistance by regulating post-translational modification of VDAC2 in pancreatic cancer . Theranostics , 10 ( 16 ), 7178 – 7192 . doi: 10.7150/thno.43093 OpenUrl CrossRef PubMed ↵ Wei , A. D. , Gutman , G. A. , Aldrich , R. , Chandy , K. G. , Grissmer , S. , & Wulff , H . ( 2005 ). International Union of Pharmacology . LII. Nomenclature and Molecular Relationships of Calcium-Activated Potassium Channels. Pharmacological Reviews , 57 ( 4 ), 463 – 472 . doi: 10.1124/pr.57.4.9 OpenUrl FREE Full Text Wen , J. , Chen , J. , Liu , D. , Xu , X. , Fan , M. , & Zhang , Z . ( 2020 ). The Eighth Edition of the American Joint Committee on Cancer Distant Metastases Stage Classification for Metastatic Pancreatic Neuroendocrine Tumors Might Be Feasible for Metastatic Pancreatic Ductal Adenocarcinomas . Neuroendocrinology , 110 ( 5 ), 364 – 376 . doi: 10.1159/000502382 OpenUrl CrossRef PubMed ↵ World Health Organization . ( 2023 ). Assessing national capacity for the prevention and control of noncommunicable diseases: Report of the 2021 global survey . World Health Organization . ↵ Wulff , H. , Miller , M. J. , Hänsel , W. , Grissmer , S. , Cahalan , M. D. , & Chandy , K. G . ( 2000 ). Design of a potent and selective inhibitor of the intermediate-conductance Ca 2+ - activated K + channel, IKCa1: A potential immunosuppressant . Proceedings of the National Academy of Sciences , 97 ( 14 ), 8151 – 8156 . doi: 10.1073/pnas.97.14.8151 OpenUrl Abstract / FREE Full Text Yachida , S. , White , C. M. , Naito , Y. , Zhong , Y. , Brosnan , J. A. , Macgregor-Das , A. M. , Morgan , R. A. , Saunders , T. , Laheru , D. A. , Herman , J. M. , Hruban , R. H. , Klein , A. P. , Jones , S. , Velculescu , V. , Wolfgang , C. L. , & Iacobuzio-Donahue , C. A . ( 2012 ). Clinical Significance of the Genetic Landscape of Pancreatic Cancer and Implications for Identification of Potential Long-term Survivors . Clinical Cancer Research , 18 ( 22 ), 6339 – 6347 . doi: 10.1158/1078-0432.CCR-12-1215 OpenUrl Abstract / FREE Full Text Yadav , D. , & Lowenfels , A. B . ( 2013 ). The Epidemiology of Pancreatitis and Pancreatic Cancer . Gastroenterology , 144 ( 6 ), 1252 – 1261 . doi: 10.1053/j.gastro.2013.01.068 OpenUrl CrossRef PubMed Web of Science Yin , L. , Pu , N. , Thompson , E. , Miao , Y. , Wolfgang , C. , & Yu , J . ( 2021 ). Improved Assessment of Response Status in Patients with Pancreatic Cancer Treated with Neoadjuvant Therapy using Somatic Mutations and Liquid Biopsy Analysis . Clinical Cancer Research , 27 ( 3 ), 740 – 748 . doi: 10.1158/1078-0432.CCR-20-1746 OpenUrl Abstract / FREE Full Text Ying , H. , Dey , P. , Yao , W. , Kimmelman , A. C. , Draetta , G. F. , Maitra , A. , & DePinho , R. A . ( 2016 ). Genetics and biology of pancreatic ductal adenocarcinoma . Genes & Development , 30 ( 4 ), 355 – 385 . doi: 10.1101/gad.275776.115 OpenUrl Abstract / FREE Full Text Yuan , S. , Almagro , J. , & Fuchs , E . ( 2024 ). Beyond genetics: Driving cancer with the tumour microenvironment behind the wheel . Nature Reviews Cancer , 24 ( 4 ), 274 – 286 . doi: 10.1038/s41568-023-00660-9 OpenUrl CrossRef Zhang , J. , Yang , J. , Lin , C. , Liu , W. , Huo , Y. , Yang , M. , Jiang , S.-H. , Sun , Y. , & Hua , R . ( 2020 ). Endoplasmic Reticulum stress-dependent expression of ERO1L promotes aerobic glycolysis in Pancreatic Cancer . Theranostics , 10 ( 18 ), 8400 – 8414 . doi: 10.7150/thno.45124 OpenUrl CrossRef PubMed Zhang , Q. , Chen , S. , Zeng , L. , Chen , Y. , Lian , G. , Qian , C. , Li , J. , Xie , R. , & Huang , K.-H . ( 2017 ). New developments in the early diagnosis of pancreatic cancer . Expert Review of Gastroenterology & Hepatology , 11 ( 2 ), 149 – 156 . doi: 10.1080/17474124.2017.1271323 OpenUrl CrossRef PubMed Zhao , C. , Gao , F. , Weng , S. , & Liu , Q . ( 2017 ). Pancreatic cancer and associated exosomes . Cancer Biomarkers , 20 ( 4 ), 357 – 367 . doi: 10.3233/CBM-170258 OpenUrl CrossRef PubMed Zheng , J. , Paniccia , A. , & Zureikat , A. H . ( 2022 ). Advances in the Surgical Treatment of Pancreatic Cancer . Surgical Pathology Clinics , 15 ( 3 ), 479 – 490 . doi: 10.1016/j.path.2022.05.003 OpenUrl CrossRef PubMed Zhu , L. , Sun , H.-T. , Wang , S. , Huang , S.-L. , Zheng , Y. , Wang , C.-Q. , Hu , B.-Y. , Qin , W. , Zou , T.-T. , Fu , Y. , Shen , X.-T. , Zhu , W.-W. , Geng , Y. , Lu , L. , Jia , H. , Qin , L.-X. , & Dong , Q.-Z . ( 2020 ). Isolation and characterization of exosomes for cancer research . Journal of Hematology & Oncology , 13 ( 1 ), 152 . doi: 10.1186/s13045-020-00987-y OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted April 30, 2025. Download PDF Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Investigating the prognostic value of KCNN4 gene expression in human pancreatic adenocarcinoma by bioinformatic analysis Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Investigating the prognostic value of KCNN4 gene expression in human pancreatic adenocarcinoma by bioinformatic analysis Syed Sajidul Islam , Md. Mehedi Hasan Tushar , Bishajit Sarkar , Ripa Moni , Umme Salma Zohora , Mohammad Shahedur Rahman bioRxiv 2025.04.26.650766; doi: https://doi.org/10.1101/2025.04.26.650766 Share This Article: Copy Citation Tools Investigating the prognostic value of KCNN4 gene expression in human pancreatic adenocarcinoma by bioinformatic analysis Syed Sajidul Islam , Md. Mehedi Hasan Tushar , Bishajit Sarkar , Ripa Moni , Umme Salma Zohora , Mohammad Shahedur Rahman bioRxiv 2025.04.26.650766; doi: https://doi.org/10.1101/2025.04.26.650766 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Bioinformatics Subject Areas All Articles Animal Behavior and Cognition (7629) Biochemistry (17660) Bioengineering (13881) Bioinformatics (41911) Biophysics (21436) Cancer Biology (18578) Cell Biology (25482) Clinical Trials (138) Developmental Biology (13371) Ecology (19887) Epidemiology (2067) Evolutionary Biology (24302) Genetics (15599) Genomics (22482) Immunology (17728) Microbiology (40363) Molecular Biology (17163) Neuroscience (88536) Paleontology (666) Pathology (2830) Pharmacology and Toxicology (4821) Physiology (7637) Plant Biology (15129) Scientific Communication and Education (2045) Synthetic Biology (4290) Systems Biology (9817) Zoology (2269)