[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-354339-105":59,"doc-detail-354339-en":134},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":127,"head_meta":129,"extra_data":131,"updated_unix":133},105,"en","multi-cohort-comparative-analysis-of-salivary-microbiotas-reveals-rural-ethiopians-harbor-a-distinct-composition-correlated-with-lower-esophageal-cancer-prevalence-esophageal-cancer-biomarker-research","Multi-cohort comparative analysis of salivary microbiotas reveals rural Ethiopians harbor a distinct composition correlated with lower esophageal cancer prevalence - Esophageal cancer biomarker research","","Esophageal cancer drives high mortality due to challenges in early diagnosis, especially across low- and middle-income settings. A secondary analysis used V4 16S rRNA sequencing from a cross-sectional study of treatment-naive, newly diagnosed patients (N=103) and healthy controls (N=108) in Ethiopia’s agricultural regions. Healthy controls showed highly diverse salivary microbiota forming two functionally distinct clusters. Cluster membership related to sex and alcohol use, not age. Both EC subtypes showed reduced diversity and increased odds of cluster 2, and classifiers generalized ESCC features to external cohorts.",{"@graph":69,"@context":126},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/multi-cohort-comparative-analysis-of-salivary-microbiotas-reveals-rural-ethiopians-harbor-a-distinct-composition-correlated-with-lower-esophageal-cancer-prevalence-esophageal-cancer-biomarker-research/354339/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/multi-cohort-comparative-analysis-of-salivary-microbiotas-reveals-rural-ethiopians-harbor-a-distinct-composition-correlated-with-lower-esophageal-cancer-prevalence-esophageal-cancer-biomarker-research/354339.png","ImageObject",300,407,{"name":92,"@type":93},"Jasmine","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-23","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118,122],{"name":109,"@type":110,"acceptedAnswer":111},"What was the main goal of this study?","Question",{"text":112,"@type":113},"To analyze whether salivary microbiota composition differs between treatment-naive esophageal cancer patients and healthy Ethiopian controls, and whether microbial features correlate with cancer risk.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were salivary microbiota profiles measured?",{"text":117,"@type":113},"Using V4 16S rRNA sequencing on saliva samples from a cross-sectional dataset of EC patients and healthy controls.",{"name":119,"@type":110,"acceptedAnswer":120},"Which findings connected the microbiota to esophageal cancer?",{"text":121,"@type":113},"EC subtypes (ESCC and EAC) were associated with loss of microbial diversity and higher probability of belonging to a specific microbial cluster (cluster 2).",{"name":123,"@type":110,"acceptedAnswer":124},"Did the predictive models work outside Ethiopia?",{"text":125,"@type":113},"Yes. Models trained on the Ethiopian cohort predicted ESCC disease status in an external China cohort, demonstrating generalization of microbial features across populations.","https://schema.org",{"og:url":83,"og:type":128,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":130,"canonical":83},"index,follow",{"doc_id":132,"site_id":62},354339,1790171197,{"code":4,"msg":5,"data":135},{"doc_id":132,"user_id":136,"nickname":92,"user_avatar":137,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":138,"file_id":139,"file_url":140,"file_type":141,"file_size":142,"view_count":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":46,"language":143,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":144,"faqs":145,"seo_title":146,"seo_description":67,"update_tm":147,"read_time":31},2336478487870,"https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","| Human Microbiome | Research Article  \nMulti-cohort comparative analysis of salivary microbiotas reveals rural Ethiopians harbor a distinct composition correlated with lower esophageal cancer prevalence  \nGirma Mulisa,1,2 Jingcheng Zhao,3 Geda Lelissa,4 Iyunoluwa J. Ademola-Popoola,5,6,7 Anastacia Marie Diaz Huemme,3 Laura S. Weyrich,5,7,8 Adane Mihret,1,9 Tufa Gemechu,10 Abate Bane,11 Roger Pero-Gascon,12 Marthe De Boevre,12 Sarah De Saeger,12,13 Tamrat Abebe,1 Jordan E. Bisanz3,6,14  \nAUTHOR AFFILIATIONS See affiliation list on p. 17.  \nABSTRACT Esophageal cancer (EC) results in high mortality due to difficulty in early diagnosis, particularly in low- and middle-income countries, including the African EC belt typified by high prevalence, early onset, and poor prognosis. While the precise etiological factors remain unknown, emerging data suggest links to the oral microbiota. In this study, we conducted a secondary analysis using V4 16S rRNA sequencing from a cross-sectional study of treatment-naive, newly diagnosed EC patients (N = 103) and healthy controls (N = 108) residing in agricultural regions of Ethiopia. We report that the salivary microbiota in the healthy Ethiopian controls is highly diverse, forming two functionally distinct community clusters differing in diversity, composition, and absolute abundance. Microbiota composition was associated with sex and alcohol consumption, but not age. Comparisons against groups from geographically distinct populations representing Tanzania, Uganda, Venezuela, and the United States (N = 641) showed that cluster 2 resembled other East African populations, while cluster 1 was unique to the Ethiopian cohort. Both EC subtypes, esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma, were associated with a loss of microbial diversity and an increased probability of having a cluster 2 microbiota (adjusted OR = 2.9 [95% CI 1.5– 5.9]). Classifiers trained to discriminate healthy and EC samples were further validated on two external EC cohorts from China (N = 161) . Models trained on the Ethiopian cohort could predict disease status in an external cohort of mid- and late-stage ESCC from China (AUROC = 0.70 ± 0.03 [mean ± SD]), demonstrating the generalization of microbial features of ESCC across populations.  \nIMPORTANCE Recent reports in North America and China have correlated oral microbiota composition with esophageal cancer, although the translation of this knowledge into the African esophageal cancer belt is hampered by a lack of data on the oral microbiota of East Africans and limited cross-cohort comparative analyses validating the utility of these biomarkers. We report that the human salivary microbiota is a meaningful biomarker of later-stage esophageal cancer that transcends geography and ethnicity and may provide utility for large-population screening. A lower-diversity and lower-abundance salivary microbiota correlated with esophageal cancer warrants further investigation to understand the role of oral microbes in mediating carcinogenesis.  \nKEYWORDS esophageal cancer, saliva, microbiome, meta-analysis  \nC ancer is the second leading cause of death worldwide, and it is estimated that one  \nin five individuals will develop cancer in their lifetime, with 1 in 9 men and 1 in 12 women dying from cancer (1) . This proportion is higher in low-and middle-income  \nEditor Marc D. Cook, North Carolina Agricultural and Technical State University, Greensboro, North Carolina, USA  \nAddress correspondence to Jordan E. Bisanz, [jordan.bisanz@psu.edu](jordan.bisanz@psu.edu).  \nTamrat Abebe and Jordan E. Bisanz contributed equally to this article.  \nauthors declare conflict of interest  \ncountries (LMICs) (2), including Ethiopia, where cancer-related mortality and incidence rates have increased in the last two decades (3) . Esophageal cancer (EC) consists of two main subtypes: esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) (4) . ESCC accounts for ","cbCaiftqGJK2r2lZ","https://ap.wps.com/l/cbCaiftqGJK2r2lZ","pdf",2104934,"English","# Abstract\n## Study design and sampling\n## Salivary microbiota clustering\n## Associations with EC subtypes\n## External validation and generalization\n# Importance","[{\"question\":\"What was the main goal of this study?\",\"answer\":\"To analyze whether salivary microbiota composition differs between treatment-naive esophageal cancer patients and healthy Ethiopian controls, and whether microbial features correlate with cancer risk.\"},{\"question\":\"How were salivary microbiota profiles measured?\",\"answer\":\"Using V4 16S rRNA sequencing on saliva samples from a cross-sectional dataset of EC patients and healthy controls.\"},{\"question\":\"Which findings connected the microbiota to esophageal cancer?\",\"answer\":\"EC subtypes (ESCC and EAC) were associated with loss of microbial diversity and higher probability of belonging to a specific microbial cluster (cluster 2).\"},{\"question\":\"Did the predictive models work outside Ethiopia?\",\"answer\":\"Yes. Models trained on the Ethiopian cohort predicted ESCC disease status in an external China cohort, demonstrating generalization of microbial features across populations.\"}]","Multi-cohort comparative analysis of salivary microbiotas reveals rural Ethiopians harbor a distinct composition correlated with lower esophageal cancer prevalence - Esophageal cancer biomarker research | PDF",1790110185]