Jussuf Kaifi
As a thoracic surgeon scientist, my laboratory is collecting tumor tissue specimens and developing xenograft mice and other models from lung cancer patients to study the progression of localized Non-Small Cell Lung Cancer (NSCLC) to metastatic disease. I aim to understand the molecular biology that drives metastatic evolution in early-stage, surgically treated patients. Because patients with metastatic NSCLC are considered incurable, studying the molecular biology of NSCLC progression to develop better treatment strategies could significantly impact cure rates for lung cancer, which remains the most common cause of cancer-related deaths in the US. My lab has developed experience with next generation RNA and DNA sequencing and bioinformatic analyses. Through my faculty appointment at the University of Missouri Institute for Data Science & Informatics (MUIDSI), I have also developed expertise in machine learning analyses in large multiomics cancer data sets. My efforts in translational cancer research have generated >140 peer-reviewed publications. I initiated investigator-initiated trials with >1,000 human biospecimens at the Truman VA (NCT03551951) and University of Missouri (NCT02838836).
Abstract
Jussuf Kaifia, Jonathan Mitchema, Amanda Millera, Yariswamy Manjunatha, Mouadh Barbiroua, Raju Murugesana, Yuanyuan Shena, Guangfu Lia, Diego Avellaa, Aadel Chaudhurib, Chi-Ren Shyua, Wesley Warrena, Peter Tonellatoa
aUniversity of MO, Columbia, MO, USA; bWashington University, St. Louis, MO, USA
Background: Non-small cell lung cancer (NSCLC) is the leading cause of cancer deaths. Patients from rural regions do worse than their urban counterparts, largely related to lack of access to cutting-edge care. Recent improvements in outcome have been demonstrated in NSCLC using targeted or immune-based therapies. In this study, we demonstrate the mutational characteristics and potential for targeted therapy in rural resectable NSCLC patients using whole exome sequencing (WES).
Materials and methods: WES was performed on tumor-adjacent normal pairs from patients undergoing resection for NSCLC in rural MO. Sequencing alignment, variant-calling, annotation, and tumor mutational burden (TMB) calculations were performed using standard methods. cBioportal and OncoKB were used for comparisons of mutational frequencies and actionable targets.
Results: A total of 34 patients underwent WES after surgical resection. The gene most frequently containing somatic variants was TP53. The median number of somatic variants was 188 (Range 11-1056) and the median TMB was 3.30 (Range 0.33-18.56) nonsynonymous mutations per Mb. Tumor stage and survival were not associated with number of variants, TMB or TP53 mutational status. We found significant concordance among the most common mutations when cross-referenced to cBioportal (R = 0.78, p<0.0001). Additionally, we found that 24% of patients had variants in actionable genes based on OncoKB annotation.
Conclusions: Rural NSCLC patients have worse outcomes. In this study, we demonstrated baseline mutational frequency and establish foundations for targeted adjuvant trials in rural NSCLC patients with specific differences. Future studies must ensure to include rural patients to maximally improve NSCLC patient outcomes.