Machine learning-based ensemble approach in prediction of lung cancer predisposition using XRCC1 gene polymorphism.

The employment of machine learning approaches has shown promising results in predicting cancer. In the current study, polymorphisms data of five single nucleotide polymorphisms (SNPs) of DNA repair gene XRCC1 (XRCC1 399, XRCC1 194, XRCC1 206, XRCC1 632, XRCC1 280) of the north Indian population along with four smoking status data is considered as an input to the proposed ensemble model to predict the risk of individual susceptibility to the lung cancer. The prediction accuracy of the proposed ensemble model for cancer predisposition was found to be 85%. The model performance is also evaluated using sensitivity, specificity, precision and the Gini index, which is found in the range of 0.83-0.87. The proposed model also outperformed in all evaluation parameters when compared with the individual Model (LM, SVM, RF, KNN and baseline neural net). Collectively, current results suggest the potential of the proposed ensemble model in predicting the risk of cancer based on XRCC1 SNPs data.Communicated by Ramaswamy H. Sarma.

Construction and characterization of an infectious molecular clone of HIV-1 subtype A of Indian origin.

India has the second highest number of HIV-1 infected people next to South Africa. The predominant proportion of HIV-1 circulating in India is of subtype C origin, with a small fraction made up of subtypes A and B. In this report, we describe the construction and characterization of the first full-length infectious molecular clone p1579A-1 HIV-1, from an HIV-1 subtype A infected person from India, using long PCR and successive ligation of the amplimers. Phylogenetic analysis of the sequence of the entire proviral DNA and LTR confirmed p1579A-1 to be an HIV-1 subtype A. Analysis of the env gene of p1579A-1 showed a conserved GPGQ motif and the absence of basic amino acids at positions 11 and 25 suggesting CCR5 coreceptor usage. Analysis of env N-linked glycosylation sites revealed fewer sites in the V1 region of envelope compared to other subtype A. Transcription factor binding site analysis of the LTR sequences identified conserved as well as unique transcription factor binding sites (TFBS) in p1579A-1. This infectious clone of HIV-1 can be useful to study the molecular mechanism of dominance of subtype C in India.