The word cancer has become scarily commonplace today; According to the World Health Organization, 9.6 million people died in 2018 due to cancer. 70% of these deaths are in low-income or middle-income countries. 1 of 6 deaths is due to cancer across the world. Given these dismal numbers, cutting-edge research is the need of the hour to delve further into the causes of this disease and design effective therapy.
Various aspects of tumours such as tumour initiation, progression, metastasis, and response to therapy have been studied using tumour cell lines. According to Esparza-López and colleagues (2019), the availability of immortalized and commercially available cell lines is not a challenge; however, there are few drawbacks of using these lines. One is possible genetic alterations due to long term culture and second, their transformation that does not allow them to reflect the precise molecular biology of cancer in patients. This calls for the use of models that closely mimic the molecular biology of tumours in patients to derive appropriate effective strategies. This can be achieved by the use of primary cancer cell culture that represents the molecular biology of cancers more closely than these commercial cell lines.
An effective approach to treat cancer is the use of “personalized cancer therapy” that uses data from the DNA/RNA expression and histopathology specific to a patient. According to Dienstmann and team (2015), cancer therapy is expected to be impacted hugely by extensive genomic profiling. There are several insights as far as alterations are concerned highlighted by The Cancer Genome Atlas (TCGA) project. While 90% of these alterations are potential targets, a treatment that targets these alterations is a challenge as these are multiple and complex genetic events. Additionally close to 80% of the variants reported are in genes that have not yet been fully understood that call for a correct understanding of how to apply these genome changes to personalized therapy.
Using only genetics to predict cancer phenotype can be possible using cancer cells derived from patient biopsies. Such testing can be possible in haematological cancers such as leukaemia as the isolation of viable cancer cells in large quantities is possible. An article published in Cancer research in 2013 by Tyner and team reported the screening of a kinase inhibitor panel on leukaemia patient samples to identify possible targets for therapy. Such an approach is also being conducted at a clinical level for acute lymphoblastic leukaemia or acute myelogenous leukaemia (clinicaltrials.gov identifier NCT: NCT01620216).
The use of primary cells to serve as a screen and diagnostic assay was reported by Kodack and colleagues in Cell reports in 2017. The establishment of primary cultures from mixed 568 patient specimens was the most successful for lung cancer samples compared to other cancers using irradiated fibroblast feeder cells along with TCM (tumour culture media). An immunofluorescence assay was developed to identify cancer cells in the mixed population. This assay was termed as “robust” as a small number of cells could be detected (around 100) that too within 48 hours to hence facilitate quick studies in oncology. This assay also could identify responses to drugs when patient-derived NSCLC cultures were exposed to appropriate drugs. Thus, cancer cell primary culture plus novel diagnostic tests as reported in this research article can pave the way to make personalized cancer therapy an efficient and effective reality soon.
José Esparza-López, Juan F. Martínez-Aguilar, María de J. Ibarra-Sánchez. Deriving Primary Cancer Cell Cultures For Personalized Therapy. Revista de investigacion clinica. 2019;71:369-80
Dienstmann, R., Jang, I. S., Bot, B., Friend, S., & Guinney, J. (2015). Database of genomic biomarkers for cancer drugs and clinical targetability in solid tumors. Cancer discovery, 5(2), 118–123. doi:10.1158/2159-8290.CD-14-1118.
Tyner, J. W., Yang, W. F., Bankhead, A., 3rd, Fan, G., Fletcher, L. B., Bryant, J., … Loriaux, M. M. (2013). Kinase pathway dependence in primary human leukemias determined by rapid inhibitor screening. Cancer research, 73(1), 285–296. doi:10.1158/0008-5472.CAN-12-1906.
Kodack, D. P., Farago, A. F., Dastur, A., Held, M. A., Dardaei, L., Friboulet, L., … Benes, C. H. (2017). Primary Patient-Derived Cancer Cells and Their Potential for Personalized Cancer Patient Care. Cell reports, 21(11), 3298–3309. doi:10.1016/j.celrep.2017.11.051