Team:Sriwijaya/Description

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Introduction

As of 2019, lung cancer is the leading cause of cancer deaths in the world. The annual medical spending for lung cancers in the United States alone costs around $80.2 billion and will not decline anytime soon.

While the prevalence of lung cancer is amongst the highest of all cancers, the lack of funds, technologies as well as trained human resources made the disease still hard to be diagnosed; especially in developing countries.

This is very concerning as a quick, reliable, accurate, and practical diagnostic method is crucial in cutting down the financial burden and mortality rates related to lung cancer.

The golden standard for lung cancer diagnosis is by histopathological examination, in which the specimen is obtained by biopsy. However, biopsy tends to be invasive and may lead to cases of misdiagnosis and refusals from the patients themselves. As a result, epidemiological study is difficult to be performed. Screening by low-dose CT-scan is another huge compounding issue related to the high cost, as well as the unavailability in lots of areas and high false-positive rates even though it is regularly examined in developed countries.

In accordance with the aforementioned disadvantages, the writer proposes a non-invasive tumor seromarker diagnostic tool, CEAgar. CEAgar is a reliable, practical and affordable diagnostic tool that does not require a highly competent healthcare employees. As mentioned previously in the problem section, the golden standard for lung cancer diagnosis is histopathological examination, in which the specimen is obtained by a highly invasive process called biopsy. That kind of procedure requires competent professionals. Therefore, besides being  extremely expensive, biopsy also cannot be done on late stage cancer patients.

With that being said, CEAgar, being minimally invasive and specific most of the time, is the best solution to the problem. CEAgar also produce a lower false positive rates in low dose CT-scan. In conclusion, this proposed model of our diagnostic tool is expected to change the world of lung cancer diagnostic algorithm as it fulfills all the rules of a good diagnostic tool (highly specific and sensitive, cheap, practical, reliable, the end result is not too far from the gold standard, and provides comfort for patients). Given that all the problems involving lung cancer diagnostic test are resolved, the morbidity and mortality rates will go down. Most importantly, the government and the people will benefit from them financially and psychosocially.

Most iGEM teams focus more on the treatments of diseases, on the other hand, the best solution to break this chain of sicknesses and deaths is by preventing the sickness from turning up at the outset. Our team provides one of the best solutions for this urgent matter, which is frequently found in other iGEM teams but not to this degree, not as huge or as imperative as this. Our team is composed by a variety of educational backgrounds and we were aiming to push this solution not only on biomolecular level but also on the social and governmental level such as revising the law on smoking, tightening the regulations of tobacco companies, and apprising the people on how crucial being aware of your state of health is.