Science Sub-Journal: Breast cancer can be detected in 1 hour! Portable cell analyzer accuracy of up to 100%!

Even under optimal conditions, accurate and timely diagnosis and division of cancer is not easy, while developing countries may face a lack of experts and equipment, and tissue biopsies can take months to obtain results, which greatly hampers early diagnosis and follow-up treatment of cancer.
to this end, an international team of researchers has designed an automated image cytometer system called CytoPAN, which can use samples obtained from fine needle punctures to accurately detect breast cancer and identify its sub-types within an hour, enabling rapid diagnosis of breast cancer.
The study, led by Jouha Min of the Center for Systems Biology at Massachusetts General Hospital in the United States, was published August 5 in the journal Science Translational Medicine under the title "CytoPAN-Portableular Cell analyses for rapid-care cancer diagnosis" in developed countries, where effective screening and early cancer detection using mammograms is common.
addition, biomarker analysis (liquid biopsy) in serum is on the rise, and genomic biomarker analysis is beginning to be used in cancer diagnosis.
, however, in low- and middle-income countries, cancer diagnosis usually occurs after advanced symptoms, such as significant lump lesions, weight loss and discomfort.
these can lead to delayed diagnosis, missed treatment options, and increased mortality.
CytoPAN, developed by the team, is a fluorescent-based portable image cell analyzer that performs multichannel imaging for cancer diagnosis and differentiation.
analyze cell images using specific algorithms to quickly, accurately, and automatically analyze cell characteristics without user input.
the system allowed multiple tests in five different channels, they also prepared freeze-dried kits containing related antibodies and optimized the analysis methods for breast cancer molecules in cell line and mouse models.
, after completing the mouse trial, the researchers applied the system to human clinical trials.
CytoPAN workflow diagram (Step 1: Take cell samples from breast cancer patients through fine needle extraction.
2: Briefly fix and semi-permeable the harvested cells.
3: Process the sample using a pre-made freeze-dried kit containing all the necessary antibodies for breast cancer diagnosis, including ER, PR, HER2 and Quad.
4: Analyze stained cells with CytoPAN devices.
5: For fast, automated data analysis, custom-developed algorithms will be used to identify cancer cells, isolate them from host cells, and extract their markup information.
6: The final diagnostic report shows a set of quantitative information, including the number of cancer cells in the patient's sample and molecular substation distribution.
) In clinical trials, studies have shown a high diagnostic rate (93%) of fine needle puncture suction (FNA) samples.
were well related to histopathology in 63 patient cell samples.
for cancer diagnosis, the diagnostic accuracy of this method is 100% (false positive rate is 0%; false negative rate is 0%).
, her2 and ER/PR receptor sublocation accuracy rates were 96% and 93%, respectively.
This method has significant advantages in many ways, first, that each sample underwent a complete treatment cycle in just one hour, second, that up to 50 cancer cells can be analyzed per sample to establish an accurate cancer diagnosis, and finally, that reliable receptor subtypes can be determined with only a small number of cancer cells.
this suggests that accurate cancer diagnosis can be achieved using only a single FNA generation cell.
, however, there are limitations to the study, as the main goal is to develop, optimize, and validate an FNA analysis system that can be used for global and remote applications.
The patient population studied may not represent populations in low- and middle-income countries, and secondly, the number of molecular biomarkers used in this study is kept to a minimum for logistical and cost reasons, and the system needs further optimization and enhancement.
researchers also envision that the technology could also speed up turnaround times between interventions and the outcomes of existing health care systems.
addition, recycling techniques can be used to apply cytoblast proteins to other areas, such as immunocellular analysis, drug trial registration, efficacy testing, or non-cancer analysis, such as liver cell analysis in liver disease.
: Source: Translational Medicine Network !-- end of content presentation -- !-- determine whether the login ends.