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MRNA-based disease diagnosis

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Workflow of blood-based mRNA test on specific cancers.

mRNA-based disease diagnosis technologies are diagnostic procedures using messenger RNAs.[1] as molecular diagnostic tools to discover the relationships between patient's DNAs and their specific biological features. The mRNA-based disease diagnosis technologies have been applied to medical field widely in recent years, especially on early diagnosis of tumors (such as renal cell carcinoma,[2] hepatocellular carcinoma,[3][4] breast cancer[5] and prostate cancer[6]). The technology can be applied to various types of samples depending on how easily the samples are accessible and whether the samples reliably contain the mRNA that related to specific diseases. For example, in hepatocellular carcinoma,[3] the tumor tissues excised during the operation are a good resource for mRNA-based test to analysis. Among those most commonly used samples , blood sample is one of the most easily accessible via minimally invasive method. degenerative diseases . Blood has been used in early diagnosis of some cancers,[7][8] such as non-small lung cancer[9] and neuroendocrine tumors.[10]

Background

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Even though modern medicine has been developing for centuries, we are still faced with quite number of medical challenges. For example, in breast cancer, three traditional expressions are routinely screened for target therapy.[11] However, for the triple negative breast cancer, none of those biomarkers can be detected leaving it with poor prognosis and high mortality. Innovative technologies like mRNA are aimed to addressing such health-related issues that still exist today.[12]

Commonly used methods in mRNA-based disease diagnosis

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RNA sequencing (RNA-seq)
RNA-seq is a high-throughput RNA sequencing technology that allows scientists to profile the entire RNA (transcriptome). Therefore, novel transcripts and gene expression level can be identified based on cDNA libraries. This method can be used for cancer diagnosis and treatment evaluation.[13]
Reverse transcription polymerase chain reaction (RT-PCR)
RT-PCR is a widely used mRNA expression detection method. It enables reverse transcription of mRNA to cDNA for further identification and qualification. In early 1992, RT-PCR was applied in PSA gene expression in peripheral blood for early prostate cancer diagnosis.[6]
Digital PCR (dPCR)
dPCR is a relatively accurate quantification method of measuring the initial concentration of mRNA targets. It can be applied to analyze genetic and epigenetic changes.[14]
In-situ hybridization (ISH)
ISH is a tissue dependent visualization method of identifying mRNA targeted in the samples. The "tissue" can be blood sample. In chronic myeloid leukemia, ISH has been applied on peripheral-blood specimens.[15]

Workflow

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A general workflow of mRNA-based disease diagnosis can be summarized as the following steps:[16][17][18]

  1. Sample collection for targeted disease: Samples for mRNA-based technology can be blood, urine, cell culture, tissue biopsy, bronchial alveola lavage, saliva, cerebrospinal fluid. The basic principle to acquire the biological samples for mRNA-based disease diagnosis is that the samples are suitable, accessible, preservable, ethical and minimum invasive. Moreover for some specific research, the samples should be collected within certain time to guarantee the quality and reduce potential contaminants.
  2. RNA processing: This step includes RNA extraction, reverse transcription to cDNA, amplification and detection. The aim to process RNA is to qualify and quantify the suspected genes for further analysis.
  3. Data analysis: After obtaining the qualified raw data from last step, bioinformatics technology will be applied to further analysis the data. There are different tools and software for data analysis, including data normalization, statistical analysis, and modeling. The aim is to select specific genes that are significantly different expressed between disease and non-disease samples. Those selected genes can be identified as diagnostic biomarkers for further validation.
  4. mRNA biomarker validation: The mRNA biomarkers are selected by bioinformatic methods. Thus, they need to be tested with real samples with reliable experiment on real identified samples with clear and accurate clinical diagnosis.
  5. Clinical application: The validated mRNA-based diagnostic method for specific diseases can be conducted along with other clinical examinations to achieve a comprehensive evaluation of the patient's status. mRNA-based examination can provide the medical workers with interpretation at RNA levels and assist on further therapy advice.

Characteristics

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High sensitivity

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Take breast cancer as an example. The sensitivity of traditional ultrasound screening for breast cancer can be 76%.[19] While with the blood-based mRNA diagnostic method, the sensitivity could be 80.6%.[20]

Qualified and quantitive measurement

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mRNA-based disease diagnostic technologies allow quantitive measurement of mRNA in the certain samples, such as leukemia[21]

Guiding personalized therapy

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As some technologies such as RNA-seq can provide the entire transcriptome of individual, the mRNA-based disease diagnosis can be developed in the landscape of personalized medicine. In HER-2 breast cancer, detection of ERBB2 mRNA expression levels is helpful in predicting response to anti-HER2-based treatments.[22]

Early diagnostic and predictive method

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As mentioned above, the mRNA-based disease diagnostic technology is more sensitive and specific to certain diseases. Even though there is no obvious symptom, the mRNA-based disease diagnostic technology can serve as screening method for early changes in RNA levels.[23] High serum metadherin mRNA expression was observed in colorectal cancer and associated with poorly differentiated histological grades[24]

References

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  1. ^ Choi, Junhong; Grosely, Rosslyn; Prabhakar, Arjun; Lapointe, Christopher P.; Wang, Jinfan; Puglisi, Joseph D. (2018-06-20). "How Messenger RNA and Nascent Chain Sequences Regulate Translation Elongation". Annual Review of Biochemistry. 87: 421–449. doi:10.1146/annurev-biochem-060815-014818. ISSN 1545-4509. PMC 6594189. PMID 29925264.
  2. ^ He, Xing; Tian, Feng; Guo, Fei; Zhang, Fangxing; Zhang, Huiyong; Ji, Jin; Zhao, Lin; He, Jingyi; Xiao, Yutian; Li, Longman; Wei, Chunmeng; Huang, Caihong; Li, Yexin; Zhang, Feng; Yang, Bo (2022-08-25). "Circulating exosomal mRNA signatures for the early diagnosis of clear cell renal cell carcinoma". BMC Medicine. 20 (1): 270. doi:10.1186/s12916-022-02467-1. ISSN 1741-7015. PMC 9404613. PMID 36002886.
  3. ^ a b Tsutsumi, M.; Sakamuro, D.; Takada, A.; Zang, S.; Furukawa, T.; Taniguchi, N. (May 1996). "Detection of a unique γ-glutamyl transpeptidase messenger RNA species closely related to the development of hepatocellular carcinoma in humans: A new candidate for early diagnosis of hepatocellular carcinoma". Hepatology. 23 (5): 1093–1097. doi:10.1002/hep.510230524. ISSN 0270-9139. PMID 8621139.
  4. ^ Omar, Haniza; Lim, Chun Ren; Chao, Samuel; Lee, Michelle Mei Lin; Bong, Chin Wei; Ooi, Edie Jian Jiek; Yu, Choon Geok; Tan, Soek Siam; Abu Hassan, Muhammad Radzi; Menon, Jayaram; Muthukaruppan, Raman; Singh, Mandeep; Nik Abdullah, Nik Azim; Ooi, Boon Phoe; Ding, Robert Phooi Huat (February 2015). "Blood gene signature for early hepatocellular carcinoma detection in patients with chronic hepatitis B". Journal of Clinical Gastroenterology. 49 (2): 150–157. doi:10.1097/MCG.0000000000000112. ISSN 1539-2031. PMID 25569223. S2CID 20567541.
  5. ^ Čelešnik, Helena (2023-02-08). "Blood-Based mRNA Tests as Emerging Diagnostic Tools for Personalised Medicine in Breast Cancer". Cancers. 15 (4): 1087. doi:10.3390/cancers15041087. PMC 9954278. PMID 36831426.
  6. ^ a b Moul, Judd W.; Merseburger, Axel S.; Srivastava, Shiv (June 2002). "Molecular markers in prostate cancer: the role in preoperative staging". Clinical Prostate Cancer. 1 (1): 42–50. doi:10.3816/cgc.2002.n.006. ISSN 1540-0352. PMID 15046712.
  7. ^ Wurdinger, Thomas; In 't Veld, Sjors G. J. G.; Best, Myron G. (2020-04-01). "Platelet RNA as Pan-Tumor Biomarker for Cancer Detection". Cancer Research. 80 (7): 1371–1373. doi:10.1158/0008-5472.CAN-19-3684. ISSN 1538-7445. PMID 32075797. S2CID 211215420.
  8. ^ Imamura, Taisuke; Komatsu, Shuhei; Ichikawa, Daisuke; Kawaguchi, Tsutomu; Miyamae, Mahito; Okajima, Wataru; Ohashi, Takuma; Arita, Tomohiro; Konishi, Hirotaka; Shiozaki, Atsushi; Morimura, Ryo; Ikoma, Hisashi; Okamoto, Kazuma; Otsuji, Eigo (2016-07-07). "Liquid biopsy in patients with pancreatic cancer: Circulating tumor cells and cell-free nucleic acids". World Journal of Gastroenterology. 22 (25): 5627–5641. doi:10.3748/wjg.v22.i25.5627. ISSN 2219-2840. PMC 4932201. PMID 27433079.
  9. ^ Rotunno, Melissa; Hu, Nan; Su, Hua; Wang, Chaoyu; Bertazzi, Pier Alberto; Caporaso, Neil; Taylor, Phil R.; Landi, Maria Teresa (2012-10-20). "A blood-based gene expression signature of early-stage non-small cell lung cancer". Journal of Clinical Oncology. 30 (30_suppl): 69. doi:10.1200/jco.2012.30.30_suppl.69. ISSN 0732-183X.
  10. ^ Malczewska, Anna; Bodei, Lisa; Kidd, Mark; Modlin, Irvin M. (2019-03-01). "Blood mRNA Measurement (NETest) for Neuroendocrine Tumor Diagnosis of Image-Negative Liver Metastatic Disease". The Journal of Clinical Endocrinology and Metabolism. 104 (3): 867–872. doi:10.1210/jc.2018-01804. ISSN 1945-7197. PMID 30358858.
  11. ^ "Targeted therapy for breast cancer". Canadian Cancer Society. Retrieved 2024-03-09.
  12. ^ Cheung, Ka Wan Emily; Choi, Sin-Yu Rachel; Lee, Lok Ting Claire; Lee, Nga Lam Ella; Tsang, Hin Fung; Cheng, Yin Tung; Cho, William Chi Shing; Wong, Elaine Yue Ling; Wong, Sze Chuen Cesar (July 2019). "The potential of circulating cell free RNA as a biomarker in cancer". Expert Review of Molecular Diagnostics. 19 (7): 579–590. doi:10.1080/14737159.2019.1633307. ISSN 1744-8352. PMID 31215265. S2CID 195066095.
  13. ^ Nie, Yue-Hua; Liu, Xiao-Dan; Huang, Ruixue; Xie, Da-Fei; Yin, Wen-Jun; Guan, Hua; Yu, Zi-Jian; Zhou, Ping-Kun (2019). "Analysis of mRNA Expression Patterns in Peripheral Blood Cells of 3 Patients With Cancer After the First Fraction of 2 Gy Irradiation: An Integrated Case Report and Systematic Review". Dose-Response. 17 (1): 1559325819833474. doi:10.1177/1559325819833474. ISSN 1559-3258. PMC 6393837. PMID 30833875.
  14. ^ Molnár, Béla; Galamb, Orsolya; Kalmár, Alexandra; Barták, Barbara Kinga; Nagy, Zsófia Brigitta; Tóth, Kinga; Tulassay, Zsolt; Igaz, Péter; Dank, Magdolna (June 2019). "Circulating cell-free nucleic acids as biomarkers in colorectal cancer screening and diagnosis - an update". Expert Review of Molecular Diagnostics. 19 (6): 477–498. doi:10.1080/14737159.2019.1613891. ISSN 1744-8352. PMID 31046485. S2CID 143434977.
  15. ^ Le Gouill, S.; Talmant, P.; Milpied, N.; Daviet, A.; Ancelot, M.; Moreau, P.; Harousseau, J. L.; Bataille, R.; Avet-Loiseau, H. (April 2000). "Fluorescence in situ hybridization on peripheral-blood specimens is a reliable method to evaluate cytogenetic response in chronic myeloid leukemia". Journal of Clinical Oncology. 18 (7): 1533–1538. doi:10.1200/JCO.2000.18.7.1533. ISSN 0732-183X. PMID 10735902.
  16. ^ Kerr, Katie; McAneney, Helen; Smyth, Laura J.; Bailie, Caitlin; McKee, Shane; McKnight, Amy Jayne (28 April 2020). "A scoping review and proposed workflow for multi-omic rare disease research". Orphanet Journal of Rare Diseases. 15 (1): 107. doi:10.1186/s13023-020-01376-x. ISSN 1750-1172. PMC 7189570. PMID 32345347.
  17. ^ Zhang, Mengjie; Hussain, Abid; Yang, Haiyin; Zhang, Jinchao; Liang, Xing-Jie; Huang, Yuanyu (1 January 2023). "mRNA-based modalities for infectious disease management". Nano Research. 16 (1): 672–691. Bibcode:2023NaRes..16..672Z. doi:10.1007/s12274-022-4627-5. ISSN 1998-0000. PMC 9258466. PMID 35818566.
  18. ^ Kerr, Katie; McAneney, Helen; Smyth, Laura J.; Bailie, Caitlin; McKee, Shane; McKnight, Amy Jayne (December 2020). "A scoping review and proposed workflow for multi-omic rare disease research". Orphanet Journal of Rare Diseases. 15 (1): 107. doi:10.1186/s13023-020-01376-x. PMC 7189570. PMID 32345347.
  19. ^ Chen, Hai-long; Zhou, Jiao-qun; Chen, Qiang; Deng, Yong-chuan (2021-07-02). "Comparison of the sensitivity of mammography, ultrasound, magnetic resonance imaging and combinations of these imaging modalities for the detection of small (≤2 cm) breast cancer". Medicine. 100 (26): e26531. doi:10.1097/MD.0000000000026531. PMC 8257894. PMID 34190189.
  20. ^ Aarøe, Jørgen; Lindahl, Torbjørn (2010). "Gene expression profiling of peripheral blood cells for early detection of breast cancer". Breast Cancer Res. 12 (1): R7. doi:10.1186/bcr2472. PMC 2880427. PMID 20078854.
  21. ^ Gabert, J.; Beillard, E.; van der Velden, V. H. J.; Bi, W.; Grimwade, D.; Pallisgaard, N.; Barbany, G.; Cazzaniga, G.; Cayuela, J. M.; Cavé, H.; Pane, F.; Aerts, J. L. E.; De Micheli, D.; Thirion, X.; Pradel, V. (December 2003). "Standardization and quality control studies of 'real-time' quantitative reverse transcriptase polymerase chain reaction of fusion gene transcripts for residual disease detection in leukemia - a Europe Against Cancer program". Leukemia. 17 (12): 2318–2357. doi:10.1038/sj.leu.2403135. ISSN 0887-6924. PMID 14562125. S2CID 8961807.
  22. ^ Schettini, Francesco; Prat, Aleix (October 2021). "Dissecting the biological heterogeneity of HER2-positive breast cancer". Breast (Edinburgh, Scotland). 59: 339–350. doi:10.1016/j.breast.2021.07.019. ISSN 1532-3080. PMC 8374722. PMID 34392185.
  23. ^ Han, Mark (2008). "Novel blood-based, five-gene biomarker set for the detection of colorectal cancer". Clin Cancer Res. 14 (2): 455–460. doi:10.1158/1078-0432.CCR-07-1801. PMID 18203981.
  24. ^ Abdel Ghafar, Muhammad Tarek; Gharib, Fatma; Abdel-Salam, Sherief; Elkhouly, Reham Abdelkader; Elshora, Ahmed; Shalaby, Khaled H.; El-Guindy, Dina; El-Rashidy, Mohamed Ali; Soliman, Nema A.; Abu-elenin, Mira Maged; Allam, Alzahraa A. (2020-04-01). "Role of serum Metadherin mRNA expression in the diagnosis and prediction of survival in patients with colorectal cancer". Molecular Biology Reports. 47 (4): 2509–2519. doi:10.1007/s11033-020-05334-5. ISSN 1573-4978. PMID 32088817. S2CID 211234528.
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