科学家发现，唾液中的细菌组成可能隐藏着一种致命食管癌的重要线索。来自南非和美国的研究人员通过分析患者唾液中的微生物，并结合机器学习技术，建立了一种区分食管癌患者与未患癌人群的预测模型。研究结果显示，基于口腔微生物特征的模型，其识别效果优于单纯依靠临床信息和人口统计特征建立的模型。这项研究为开发简单、低成本的辅助筛查工具提供了新的思路。
这项研究由南非金山大学悉尼·布伦纳分子生物科学研究所与美国哥伦比亚大学的科学家共同开展，成果发表于《Communications Medicine》期刊。研究聚焦的疾病是食管鳞状细胞癌（ESCC），这是食管癌的一种主要类型，在东非和南部非洲部分地区，以及中国和伊朗的一些地区发病率较高。科学家长期以来一直试图解释这种疾病为何会在特定地理区域集中出现，其背后的遗传、环境和生活方式因素仍未完全明确。
食管鳞状细胞癌与另一种食管癌——食管腺癌——存在一定差异。后者与胃酸反流、肥胖等因素的关联较为明确，而前者的致病机制更加复杂，已知风险因素尚不足以解释全部病例。研究人员指出，这种癌症也可能较早发生，患者确诊时的平均年龄约为50岁，约18%的患者在40岁之前就已发病。
此前的研究已经发现，吸烟、大量饮酒、农村居住环境、受教育程度较低，以及使用生物质燃料或其他家庭燃料等因素，都与食管鳞状细胞癌的发生风险有关。然而，这些因素仍然无法充分解释部分地区较高的发病率，也不能解释为何一些没有明显相关暴露经历的人同样会患病。
为寻找新的疾病标志，研究团队将注意力转向口腔微生物组，也就是生活在口腔中的细菌等微生物群落。研究人员对唾液样本中的细菌DNA进行测序，发现食管鳞状细胞癌患者与未患癌的对照人群之间存在明显的细菌组成差异。进一步分析发现，部分细菌在患者唾液中更为丰富，其中包括具核梭杆菌。这种细菌此前也曾在其他癌症相关研究中受到关注。
研究团队随后利用细菌测序数据和机器学习方法，建立了用于区分患者与对照人群的预测模型。结果显示，纳入口腔微生物特征后，模型的区分能力优于仅使用临床和人口统计信息的模型。这意味着，唾液中的细菌组成可能成为现有风险评估方法之外的一种补充信息。
不过，研究人员强调，目前的结果并不能证明这些细菌会直接导致食管癌。另一种可能是，细菌组成的变化其实是癌症发生后的结果。例如，随着肿瘤逐渐生长，食管可能受到挤压，导致食物通过困难、吞咽功能受到影响，而这些变化又可能间接改变口腔微生物环境。
即便细菌变化只是疾病造成的结果，也可能具有临床价值。食管阻塞通常是逐渐发展的，在患者因严重吞咽困难前往医院之前，身体可能已经出现一段时间的变化。如果唾液中的微生物特征能够反映这些变化，医生就有机会更早发现需要进一步检查的人群，并及时安排内镜检查。
研究人员因此认为，未来可以尝试开发唾液检测或口腔拭子检测工具，用于辅助识别需要接受食管内镜检查的人，尤其是在医疗资源不足、专科检查不易获得的地区。这种方法有望降低初步筛查的成本，并帮助医疗系统更合理地安排检查资源。但目前的模型尚未被确立为一种成熟的早期癌症检测手段，唾液检测也不能取代内镜等正式诊断方法。
接下来，研究团队还需要在独立人群中验证模型的可靠性。口腔微生物组会受到地理环境、饮食习惯和其他环境因素影响，因此，在一个地区建立的预测模型未必能够直接适用于其他人群。研究人员计划进一步比较确诊食管鳞状细胞癌的患者、健康人群，以及患有良性食管疾病的人群。由于一些良性疾病同样可能导致吞咽困难，这些比较有助于判断相关细菌特征究竟与癌症本身有关，还是更多反映食管通道受阻等一般性变化。
与此同时，研究人员还在寻找这种癌症背后的遗传和环境线索。一项研究方向是分析肿瘤细胞中的基因突变特征。某些化学物质、污染物、烟雾暴露或水源污染可能在DNA中留下具有辨识度的损伤模式。通过分析这些突变特征，科学家或许能够进一步追踪与疾病有关的环境因素，并解释为何某些地区的发病率特别高。
这项研究目前仍处于探索阶段，其重要意义在于发现了唾液微生物特征与食管鳞状细胞癌之间的关联，并为后续开发非侵入性辅助筛查方法提供了基础。未来能否将其转化为实际临床工具，还取决于独立人群验证、检测准确性评估，以及能否排除其他食管疾病和环境因素的干扰。对于这种往往在病情进展后才被发现的癌症而言，如果唾液检测最终能够帮助医生更早锁定需要进一步检查的人群，将有望为高风险地区的疾病筛查提供一种更加便捷的补充手段。
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Scientists have found that bacteria in saliva may have hidden important clues to a deadly oesophagus cancer. Researchers from South Africa and the United States have developed a predictive model that distinguishes oesophagus from uncancered populations by analysing microorganisms in patients ' s saliva and combining machine learning techniques. The results show that models based on oral microbiological characteristics are better identified than models based solely on clinical information and demographic characteristics. The study provides new ideas for the development of simple, low-cost supporting screening tools.
The study was carried out by the Sydney Brenner Institute of Molecular Biosciences of the University of Kinsan, South Africa, in collaboration with scientists from Columbia University in the United States, and its results were published in the Journal Communications Medicine. Focused diseases are oesophagus carcinoma (ESCC), a major type of oesophagus cancer, with higher incidence in parts of Eastern and Southern Africa, as well as in parts of China and Iran. Scientists have long sought to explain why the disease is concentrated in specific geographical areas, and the underlying genetic, environmental and lifestyle factors are still not fully clear.
There is a difference between oesophagus cell cancer and another oesophagus cancer — oesophagus cancer. The latter are more clearly linked to factors such as gastric acid retortion and obesity, which are more complex in their disease-causing mechanisms and where the known risk factors are not sufficient to explain all cases. Researchers point out that this cancer may also occur earlier, with the average age at the time of diagnosis being around 50 years, and about 18 per cent of patients have had an illness before the age of 40.
Previous studies have found that factors such as smoking, high levels of alcohol consumption, rural living conditions, low levels of education and the use of biomass or other household fuels are all associated with the risk of edible cell cancer. However, these factors still do not fully explain the high incidence in some areas or why some people with no apparent relevant exposure experience are similarly ill.
To find new signs of disease, the research team turned its attention to oral micro-organisms, i.e. micro-organisms such as bacteria living in the mouth. Researchers sequenced the bacterial DNA in saliva sample and found significant differences in bacterial composition between oesophagus carcinoma patients and those in control without cancer. Further analysis found that part of the bacteria was more abundant in the saliva of the patient, including a nucleotobacteria. This bacteria has also previously received attention in other cancer-related studies.
The research team then developed a predictive model for distinguishing patients from the control population, using bacterial sequencing data and machine learning methods. The results show that, by incorporating oral microbiological characteristics, models are better differentiated than models using only clinical and demographic information. This means that bacterial composition in saliva may be a supplementary information to existing risk assessment methods.
However, the researchers stress that the current results do not prove that these bacteria directly cause edible cancer. Another possibility is that changes in bacteria are actually the result of cancer. For example, as tumours grow, the oesophagus can be squeezed, resulting in food being affected through difficulty, swallowing, and these changes may indirectly change the oral microbiological environment.
Even though bacterial changes are only the result of disease, they can be of clinical value. Absorption is usually progressive and physical changes may have occurred for some time before the patient reaches the hospital due to severe swallowing difficulties. If microbiological characteristics in saliva reflect these changes, doctors are given an opportunity to identify at an earlier stage the population in need of further examination and to arrange for an endoscopy in a timely manner.
Researchers are therefore of the view that in the future an attempt could be made to develop saliva testing or oral swab testing tools to assist in identifying those who need an endoscope examination, especially in areas where medical resources are inadequate and specialized examinations are not easily available. This approach is expected to reduce the cost of initial screening and help the medical system to rationalize screening resources. However, the current model has not yet been established as a mature early cancer detection tool and saliva testing cannot replace formal diagnostic methods such as endoscopy.
Next, the research team needs to verify the reliability of the model among independent populations. Oral micro-organisms can be influenced by geographical circumstances, dietary habits and other environmental factors, so predictive models established in one area may not be directly applicable to other populations. Researchers plan to make further comparisons between patients with cuisine cell cancer, the healthy population and the population suffering from benign cuisine diseases. Since some benign diseases may also lead to ingestion difficulties, these comparisons help to determine whether the bacterial characteristics are related to cancer itself or more reflective of general changes such as obstructing the oesophagus.
At the same time, researchers are looking for genetic and environmental clues behind this cancer. One study is directed towards the analysis of genetic mutations in tumor cells. Certain chemical substances, pollutants, smoke exposure or water contamination may leave a recognized pattern of damage in DNA. By analysing these mutations, scientists may be able to further track the environmental factors associated with disease and explain why the incidence is particularly high in some regions.
The study, which is still in the exploratory phase, is significant in that it discovers the link between saliva microbiological characteristics and oesophagus cell cancer and provides a basis for the subsequent development of non-intrusive assistive screening methods. Future translation into practical clinical tools will also depend on independent crowd validation, testing accuracy assessments and the exclusion of interference with other cuisine diseases and environmental factors. For such cancers, which are often detected after the disease progresses, saliva testing is expected to provide an easier and complementary means for disease screening in high-risk areas if it ultimately helps doctors to target populations more early.
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