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Abstract

Lung cancer has the one of the highest incidence and death rate among all types of cancer. When
lung cancer patients are diagnosed at the late stage, it is rarely curable; thus, early diagnosis is
one way to improve lung cancer patients’ survival rate. Detection of circulating lung cancer cells
would represent an improved diagnostic tool to indicate metastasising tumours at an early stage,
contributing to better prognosis of the disease. To address this issue, this dissertation aimed to
design aptamers for lung cancer cells, as alternatives to antibodies for detection of circulating
cancer cells with stem cells characteristics as a novel tool for diagnosis and following the
progression of lung cancer.
Aptamers are single stranded DNA or RNA molecules, capable of forming three-dimensional
(3D) structures fitting the target molecules. Aptamers are chemically synthesized and have long
shelf life and high specificity and affinity for the target proteins and/or cells. They are more robust
for different types of modification and conjugation compared with antibodies of the same
specificity. With the Cell-based Systematic Evolution of Ligands by EXponential enrichment
(Cell-based SELEX) technique, aptamers can also be readily developed for any types of cells of
interest. The resulting aptamers recognize their target molecules in their native state in the original
cellular context. Our approach focuses on aptamer development for whole non-small cell lung
cancer (NSCLC) cells expressing the stem cell surface marker CD90.
The human adenocarcinoma cell line A549 was used as a target in seven SELEX rounds. The last
round included selection for a cell population positive for CD90 expression.
We identified the aptamer A155_18, which had good characteristics for binding to cell line A459
in terms of high affinity, consensus motifs and structural stability. The final selection analysis
was based on applying three independent bioinformatics approaches in parallel, two of them
resulting in selecting the same candidates with the best binding characteristics.
This aptamer was then compared with the reported A459 cell-binding aptamer S6, which served
as positive control. The selected pool was used for sequencing and subjected to three independent
bioinformatics analyses. The calculated dendrogram showed that aptamers A155_18 and the S6
have a close structural relationship. According to one of the used sequence analysis tool, called
MEME, they share two unique motifs, which are not present in other identified sequences.
Noteworthy, as A459 cells were binding both, aptamer A155_18 and the CD90 antibody, a partial
stemness characteristics of the primary A459 cell line, or more likely indicates on the presence of
stem cell-like subpopulation within the primary cultured non-small cell lung cancer cell line.
In conclusion, in this work we successfully developed a novel aptamer A155_18 binding to CD90-
positive A549 lung cancer cells. The novelty of our approach is the in silico selection of aptamers
with emphasis on bioinformatics–based prediction of secondary structures and theoretical
physicochemical properties, enabling the direct selection of the most appropriate oligonucleotide
aptamer. Besides early diagnosis, this aptamer could also be used in search for identification of
other target proteins on NSCLC cell surface and potentially contribute to biomarker discovery for
lung cancer.