Delhi researchers develop an algorithm to detect rare cells
What in news:
· A new algorithm developed by Delhi-based researchers makes it easy to find rare cells from a very large pool of cells in a matter of seconds.
· The algorithm — Finder of Rare Entities (FiRE) — assigns a rareness score to each cell that is computed based on the gene expression profile of about twenty thousand genes.
· Cells having scores above a certain threshold are reported as rare cells.
· Besides being fast, initial studies show that the new algorithm has superior sensitivity and specificity compared with existing methods.
· Circulating tumour cells, cancer stem cells, antigen-specific T cells, circulating endothelial cells are a few examples of rare cells.
· Rare cell populations such as circulating tumour cells can shed light on the process of cancer metastasis (spreading of cancer to other parts of the body) thus providing invaluable information for early detection and clinical management of the disease.
New cell type
· While testing the efficacy of the algorithm using mouse brain cells taken from a specific region, the four-member from Indraprastha Institute of Information Technology (IIIT-Delhi), Delhi discovered a new sub-type of pars tuberalis cell lineage.
· The authors have linked this newly found cell type to the development of the pituitary gland. The results are published in the journal Nature Communications.
· “FiRE uses sketching, which is a variant of locality-sensitive hashing, to assign rarity to each cell.
· The hashing technique tends to put cells with similar properties together,” says Prashant Gupta from IIT Delhi and one of the first authors of the paper.
· The FiRE algorithm makes searching for rare cells in large-scale single cell messenger RNA datasets tractable
· We used the gene expression of each cell to find the rare cells.
· The drop-seq, a state-of-the-art technique, allowed us to read out the gene expression profiles of thousands of cells in a fairly short time and then compared the profiles to find the rare cells.”
· The researchers used five data sets to test the algorithm. In the case of peripheral blood containing 0.3% megakaryocytes, the gene expression of about 68,000 different cells was compared, and rare cell populations with different grades of rarity showed up. The cluster with the rarest cells comprised of only megakaryocytes, thus validating the algorithm.
· In a simulation experiment to evaluate the performance of FiRE algorithm, the gene expression profiles of two types of cells were mixed in vitro.
· And by increasing the percentage of one cell type, the team tested the precision and sensitivity of FiRE and other existing algorithms to correctly identify the rare cells.
· The sensitivity of the FiRE algorithm was higher than the rest even when rare cells comprised 0.5% of the population.
· “When they constituted 2.5%, FiRE could identify rare cells with 85% accuracy, far higher than the other algorithms,” says Aashi Jindal from IIT Delhi and the other first author of the paper.
· Cancer refers to the abnormal growth of cell tissue.
· Tumours are usually divided into benign and malignant.
· A benign tumour is localised, develops slowly and does not usually result in the patient’s death.
· Malignant or cancerous tumours develop more rapidly. They are not localised and are often fatal for the patient.
· Cancer begins with a genetic defect.
· Human’s genetic factors, meaning genes, are located within the cell structures called chromosomes.
· Genes control cell functions, such as their distribution. Genes may undergo changes, or mutations, if the cell’s regulatory system fails.
Expected prelims question
Consider the following statements
1. Cancer refers to the abnormal growth of cell tissue.
2. Cancer is communicable diseases
Which of the above statements is/are correct?
a) Only 1
b) Only 2
c) Both 1 and2
d) None of the above
Ans – a
Expected mains question
What do you mean by cancer? mention its different types and add a note on role of technology playing to detect and cure this life threatening disease.