Background: A growing body of evidence has shown the association between tuberculosis (TB) infection and lung cancer. However, the possible effect of strain-specific behavior of Mycobacterium tuberculosis (M.tb) population, the etiological agent of TB infection in this association has been neglected. In this context, this study was conducted to investigate this association with consideration of the genetic background of strains in the M.tb population.
Results: We employed the elastic net penalized logistic regression model, as a statistical-learning algorithm for gene selection, to evaluate this association in 129 genes involved in TLRs and NF-κB signaling pathways in response to two different M.tb sub-lineage strains (L3-CAS1and L 4.5). Of the 129 genes, 21 were found to be associated with the two studied M.tb sub-lineages. In addition, MAPK8IP3 gene was identified as a novel gene, which has not been reported in previous lung cancer studies and may have the potential to be recognized as a novel biomarker in lung cancer investigation.
Conclusions: This preliminary study provides new insights into the mechanistic association between TB infection and lung cancer. Further mechanistic investigations of this association with a large number of M.tb strains, encompassing the other main M.tb lineages and using the whole transcriptome of the host cell are inevitable.
Keywords: Elastic net penalized logistic regression; Lineage; Lung Cancer; Mycobacterium tuberculosis.