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Radiation therapy (RT) in some cases results in a systemic anticancer response known as the abscopal effect. Multiple hypotheses support the role of immune activation initiated by RT-induced DNA damage. Optimal radiation dose is necessary to promote the cGAS-STING pathway in response to radiation and initiate an IFN-1 signaling cascade that promotes the maturation and migration of dendritic cells to facilitate antigen presentation and stimulation of cytotoxic T cells. T cells then exert a targeted response throughout the body at areas not subjected to RT. These effects are further augmented through the use of immunotherapeutic drugs resulting in increased T-cell activity. Tumor-infiltrating lymphocyte presence and TREX1, KPNA2 and p53 signal expression are being explored as prognostic biomarkers.

Tumor mutation burden (TMB) is often used as a biomarker for immunogenicity and prerequisite for immune checkpoint inhibitor (ICI) therapy. However, it is becoming increasingly evident that not all tumors with high TMB respond to ICIs as expected. It has been shown that the ability of T-cells to infiltrate the tumor microenvironment and elicit a specific immune response is dependent not only on the TMB, but also on intra-tumor heterogeneity and the fraction of low-frequency subclonal mutations that make up the tumor. High intra-tumor heterogeneity leads to inefficient recognition of tumor neoantigens by T-cells due to their diluted frequency and spatial heterogeneity. Clinical studies have shown that tumors with a high degree of intra-tumor heterogeneity respond poorly to ICI therapy, and previous cytotoxic treatment may increase the intra-tumor heterogeneity and render second-line ICI therapy less effective. This paper reviews the role of ICI therapy when following chemotherapy or radiation to determine if they may be better suited as first-line therapy in patients with high TMB, low intra-tumor heterogeneity, and high PD-1, PD-L1, or CTLA-4 expression.

Background Oncopanel genomic testing, which identifies important somatic variants, is increasingly common in medical practice and especially in clinical trials. Currently, there is a paucity of reliable genomic reference samples having a suitably large number of pre-identified variants for properly assessing oncopanel assay analytical quality and performance. The FDA-led Sequencing and Quality Control Phase 2 (SEQC2) consortium analyze ten diverse cancer cell lines individually and their pool, termed Sample A, to develop a reference sample with suitably large numbers of coding positions with known (variant) positives and negatives for properly evaluating oncopanel analytical performance. Results In reference Sample A, we identify more than 40,000 variants down to 1% allele frequency with more than 25,000 variants having less than 20% allele frequency with 1653 variants in COSMIC-related genes. This is 5–100× more than existing commercially available samples. We also identify an unprecedented number of negative positions in coding regions, allowing statistical rigor in assessing limit-of-detection, sensitivity, and precision. Over 300 loci are randomly selected and independently verified via droplet digital PCR with 100% concordance. Agilent normal reference Sample B can be admixed with Sample A to create new samples with a similar number of known variants at much lower allele frequency than what exists in Sample A natively, including known variants having allele frequency of 0.02%, a range suitable for assessing liquid biopsy panels. Conclusion These new reference samples and their admixtures provide superior capability for performing oncopanel quality control, analytical accuracy, and validation for small to large oncopanels and liquid biopsy assays.

Clinical laboratories routinely use formalin-fixed paraffin-embedded (FFPE) tissue or cell block cytology samples in oncology panel sequencing to identify mutations that can predict patient response to targeted therapy. To understand the technical error due to FFPE processing, a robustly characterized normal cell line was used to create FFPE samples with four different pre-tissue processing formalin fixation times. A total of 96 FFPE sections were then distributed to different laboratories for targeted sequencing analysis by four oncopanels, and variants resulting from technical error were identified. Tissue sections that failed more frequently showed low cellularity, lower than recommended library preparation DNA input, or target sequencing depth. Importantly, sections from block surfaces were more likely to show FFPE-specific errors, akin to “edge effects” seen in histology, and the depth of formalin damage was related to fixation time. To assure reliable results, we recommend avoiding the block surface portion and restricting mutation detection to genomic regions of high confidence.

SUMMARYThe primary objective of the FDA-led Sequencing and Quality Control Phase 2 (SEQC2) project is to develop standard analysis protocols and quality control metrics for use in DNA testing to enhance scientific research and precision medicine. This study reports a targeted next generation sequencing (NGS) method that enables more accurate detection of actionable mutations in circulating tumor DNA (ctDNA) clinical specimens. This advancement was enabled by designing a synthetic internal standard spike-in for each actionable mutation target, suitable for use in NGS following hybrid-capture enrichment and unique molecular index (UMI) or non-UMI library preparation. When mixed with contrived ctDNA reference samples, internal standards enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position, in each sample. True positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity.

Summary The primary objective of the FDA-led Sequencing and Quality Control Phase 2 (SEQC2) project is to develop standard analysis protocols and quality control metrics for use in DNA testing to enhance scientific research and precision medicine. This study reports a targeted next-generation sequencing (NGS) method that will enable more accurate detection of actionable mutations in circulating tumor DNA (ctDNA) clinical specimens. To accomplish this, a synthetic internal standard spike-in was designed for each actionable mutation target, suitable for use in NGS following hybrid capture enrichment and unique molecular index (UMI) or non-UMI library preparation. When mixed with contrived ctDNA reference samples, internal standards enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position in each sample. True-positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity.

Background: Detection of rare variants in traditional and liquid biopsies is becoming increasingly important for cancer diagnosis, monitoring and treatment. Next Generation Sequencing (NGS) has the capacity to detect known and novel variants in small biological samples with a high level of sensitivity. However, the limit of detection is affected by sample DNA concentration and integrity, technical error and number of unique molecules captured and sequenced (library complexity). Unique molecular identifiers (UMl) and random fragment end analysis commonly are used to measure complexity yet both are reported to have systematic biases leading to a non-random read distribution when measured, altering interpretation of results and potentially skewing data. Here we describe the use of a spike in complexity calibration ladder comprising synthetic DNA internal standard competitors (IS) as an orthogonal measure of library complexity. Methods: An Endogenous Complexity Calibration Ladder (ECCL) comprising multiple unique synthetic IS at different concentrations was created. All ECCL IS share homology with each other and endogenous human SCGB1A1 sequence but each contain nucleotide changes at different positions along the sequence string so that they can be distinguished. The ECCL was mixed with several IS targeting different TP53 exons in a fixed proportion. The ECCL/TP53 IS mixture is designed to be used in either amplicon or hybrid-capture library preparation. Here, amplicon libraries were generated. Molecule numbers and ratios between IS were determined using deep sequencing of multiple replicates. The ECCL/TP53 IS mix was spiked into a commercial human gDNA prior to NGS library preparation. Serial dilutions (1.5-, 3-, 6-, 12- and 24-fold) and intentional addition of inhibitors were conducted to stress and test the system. The ECCL/TP53 IS mixture also was spiked into gDNA from 60 primary airway epithelial cell (AEC) specimens prior to library preparation and NGS to measure TP53 variant fraction while controlling for complexity. Results: Observed complexity measured using the ECCL was close to expected for each serially diluted mixture of gDNA and ECCL/TP53 IS. The precision of complexity measurement for less dilute and less inhibited samples was limited by absence of finer titration of the least concentrated IS in ECCL. Use of ECCL enabled measurement of inter-sample variation in complexity among the 60 AEC specimens. Conclusions: The ECCL controls for both sample and library specific variation in complexity, and enables better estimation of the lower limit of detection for variant allele fraction (VAF). Additionally, it is compatible with the use of target specific IS which allow for improved measurement of technical sequencing error. The variation in complexity observed in primary AEC gDNA samples demonstrates the need to account for this when assessing rare variant allele fraction. Citation Format: Erin L. Crawford, Tian Chen, Daniel J. Craig, James C. Willey. Use of a synthetic spike-in ladder to measure NGS library complexity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2286.

Background: Lung cancer is the leading cause of cancer-related death in men and women in the United States. Based on evidence from controlled trials in the United States and Europe that low dose CT (LDCT) screening significantly reduces lung cancer mortality, the United States Preventative Services Tasks Force (USPSTF) recommends LDCT screening for individuals with high demographic risk based on age and smoking history. However, a large fraction of lung cancers occur in individuals who do not meet LDCT screening threshold criteria. Thus, there is a need for biomarkers that supplement demographic factors to more accurately detect those at highest lung cancer risk and include additional individuals who will benefit from LDCT screening. An initial study from this lab demonstrated that TP53 mutations with 0.05-1.0% variant allele fraction (VAF) were significantly more prevalent (p Methods: AEC specimens were prospectively collected through the National Cancer Institute Early Detection Research Network (EDRN) program from 60 subjects at high demographic risk for lung cancer by bronchoscopic brush biopsy at Vanderbilt University Medical Center. Genomic (g)DNA was extracted from each AEC specimen and stored at -80 degrees Celsius. Subjects matched for age and smoking history who subsequently did or did not develop lung cancer were identified and gDNA specimens, blinded with respect to cancer status, were shipped to the University of Toledo. gDNA specimens were quantified and 50,000 gDNA copies were included in each NGS library preparation. Synthetic DNA internal standards (IS) were prepared for multiple lung cancer driver mutations within the TP53 gene and mixed with each AEC gDNA specimen prior to competitive multiplex PCR NGS library preparation. By controlling for technical error, this approach enables reliable detection of mutations with VAF as low as 5 x 10-4 (0.05%) (Craig et al, BMC Cancer, 2019). Results: Following library preparation and sequencing on Illumina Novaseq, there was sufficient library complexity to detect TP53 VAF 90% of AEC specimens. The data are currently in pipeline analysis. After analysis is complete, VCF files will be sent to Vanderbilt for unblinding and validation of the biomarker. Conclusions: Based on preliminary data, we expect that sufficient AEC gDNA is available from most subjects enrolled in the EDRN program for TP53 low VAF biomarker analysis, and the previously reported method (Craig et al, BMC Cancer, 2019) is reliable and feasible. The current study should provide additional information regarding validity of the biomarker. Citation Format: Daniel J. Craig, Erin L. Crawford, Pierre P. Massion, Thomas Morrison, James C. Willey. Low frequency TP53 mutations in airway epithelial cells serve as lung cancer risk biomarker [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2525.

BackgroundStandardized Nucleic Acid Quantification for SEQuencing (SNAQ-SEQ) is a novel method that utilizes synthetic DNA internal standards spiked into each sample prior to next generation sequencing (NGS) library preparation. This method was applied to analysis of normal appearing airway epithelial cells (AEC) obtained by bronchoscopy in an effort to define a somatic mutation field effect associated with lung cancer risk. There is a need for biomarkers that reliably detect those at highest lung cancer risk, thereby enabling more effective screening by annual low dose CT. The purpose of this study was to test the hypothesis that lung cancer risk is characterized by increased prevalence of low variant allele frequency (VAF) somatic mutations in lung cancer driver genes in AEC.MethodsSynthetic DNA internal standards (IS) were prepared for 11 lung cancer driver genes and mixed with each AEC genomic (g) DNA specimen prior to competitive multiplex PCR amplicon NGS library preparation. A custom Perl script was developed to separate IS reads and respective specimen gDNA reads from each target into separate files for parallel variant frequency analysis. This approach identified nucleotide-specific sequencing error and enabled reliable detection of specimen mutations with VAF as low as 5 × 10− 4(0.05%). This method was applied in a retrospective case-control study of AEC specimens collected by bronchoscopic brush biopsy from the normal airways of 19 subjects, including eleven lung cancer cases and eight non-cancer controls, and the association of lung cancer risk with AEC driver gene mutations was tested.ResultsTP53 mutations with 0.05–1.0% VAF were more prevalent (p ConclusionsApplication of SNAQ-SEQ to measure mutations in the 0.05–1.0% VAF range enabled identification of an AEC somatic mutation field of injury associated with lung cancer risk. A biomarker comprising TP53, PIK3CA, and BRAF somatic mutations may better stratify individuals for optimal lung cancer screening and prevention outcomes.

Background: Lung cancer is the leading cause of cancer-related death in men and women, and cigarette smoking is the most significant preventable risk factor. Early detection through annual low dose CT screening reduces mortality but has low positive predictive value and specificity, in part due to low lung cancer incidence ( Methods: Synthetic DNA internal standards (IS) were prepared for each of 11 lung cancer driver genes and mixed with each AEC genomic (g)DNA specimen prior to competitive multiplex PCR amplicon NGS library preparation. A custom Perl script was developed to separate IS reads and respective specimen gDNA reads from each target into separate files for parallel variant frequency analysis. This approach enabled reliable detection of mutations with VAF as low as 5 x 10-4 (0.05%). This method was then applied in a retrospective case-control study. Specifically, AEC specimens were collected by bronchoscopic brush biopsy from the normal airways of 19 subjects, including eleven lung cancer cases and eight non-cancer controls, and the association of lung cancer risk with AEC driver gene mutations was tested. Results: TP53 mutations with 0.05-1.0% VAF were more prevalent (p Conclusions: Measurement of very low frequency mutations in the 0.05-1.0% VAF range enabled identification of an AEC somatic mutation field of injury associated with lung cancer risk. A biomarker comprising TP53, PIK3CA, and BRAF somatic mutations may better stratify individuals for optimal lung cancer screening and prevention outcomes. Citation Format: Daniel J. Craig, Thomas Morrison, Sadik Khuder, Erin L. Crawford, Leihong Wu, Joshua Xu, Thomas M. Blomquist, James C. Willey. TP53, PIK3CA, and BRAF somatic mutations in airway epithelial field of injury associated with lung cancer risk [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4609.

Background: Identification of actionable mutations in circulating tumor DNA (ctDNA) enables gene-targeted therapy of solid tumors based on a simple blood test. NGS methods that attach a unique molecular identifier (UMI) to each DNA molecule reduce variant allele fraction (VAF) limit of detection (LOD) to 0.5% was >95%, but reproducibility at 0.1-0.5% VAF was about 70%. Given limited value of UMI NGS when size of ctDNA specimen restricted VAF LOD to 0.5%, we tested the hypothesis that synthetic internal standard (IS) spike-in molecules provide reliable alternative quality control while eliminating UMI-imposed sequencing burden. Methods: We synthesized IS for 61 actionable mutations, cloned them into pUC vectors, confirmed each IS to be wild-type sequence, linearized, quantified abundance and combined at a 1:1 genome copy mixture. An aliquot of IS mixture was added to the ctDNA reference material at 1:1 genome copy prior to library prep, followed by Illumina HiSeq sequencing, separation of target from IS reads using custom splitter, then pipeline analysis on Qiagen CLC Genomics Workbench. Results: Analysis of each target relative to IS reliably identified base-substitution sequencing errors at each measured actionable mutation site and determined that VAF for each was 200,000 reads per target in each sample, with analysis relative to IS spike-ins, 20,000 reads was sufficient (10,000 reads for the specimen and 10,000 reads for the spike-in). Because the IS spike-in molecules were validated to be wild-type, any variants were assumed to be due to technical error. Thus, a z-score comparing sequence count for a) specimen wild-type, b) specimen mutant, c) IS wild-type, and d) IS mutant enabled calculation of confidence level regarding each biological variant call. Conclusion: Preliminary data indicate that IS spike-in mixtures enable reliable analysis of ctDNA mutation fraction to LOD of 0.5% without need for UMI. Disclaimer: The views expressed here are those of the authors only and do not necessarily express the views/policies of the FDA. Citation Format: Daniel J. Craig, Erin L. Crawford, Joshua Xu, Thomas M. Blomquist, Leihong Wu, Thomas Morrison, James C. Willey. Novel method for NGS analysis of actionable mutations in circulating tumor DNA specimens: improved quality control and 20-fold lower sequencing required [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 432.

Background: Inter-individual variation in risk for lung cancer is based on variation in both exposure to environmental factors and genetic predisposition. As such, it is reasonable to hypothesize that prevalence of mutations in the airway epithelium will vary based on the combined effects of these lung cancer risk factors. Genes most commonly mutated in non-small cell lung cancer were recently reported from The Cancer Genome Atlas (TCGA) project. The purpose of this study was to use targeted deep sequencing to assess the prevalence of these mutations in bronchial epithelial cells (BEC) of individuals at high demographic risk for lung cancer. Methods: We enrolled 19 individuals with varying demographic risk for lung cancer, who were undergoing standard-of-care bronchoscopy into an IRB-approved research study in which we collected 1-5 million BEC via bronchoscopic brush biopsy and extracted genomic DNA. 10 subjects were smokers with lung cancer, 6 subjects were smokers without lung cancer, and 3 subjects were non-smokers without lung cancer. For targeted deep sequencing, we prepared synthetic spike-in competitive internal standards for each of 12 gene loci commonly mutated in lung cancer based on TCGA results and combined them into an IS mixture (ISM). DNA aliquots from each patient were quantified and mixed with equivalent genome equivalents of ISM prior to library preparation to control for technical artifacts associated with library preparation and NGS platform-specific error. The DNA input varied depending on sample quantity; there were 5 samples with 50,000 genome copies loaded, 12 samples with 100,000 genome copies loaded, and 2 samples with 1 million genome copies loaded. This approach enabled reliable measurement of 95% confidence limits of variant allele frequency (VAF), controlled for technical sequencing error, and allowed confident call of variants at a VAF of 0.1% and lower. Libraries for specimens from each of the 19 subjects were first sequenced using the Illumina MiSeq platform to ensure equal coverage across targets and samples. Deeper sequencing was then obtained using the Illumina NextSeq platform. Results: Preliminary results showed that smokers harbored mutations up to 1.6% in gene loci associated with non-small cell lung cancer according to TCGA, while none were identified in non-smoking controls. Conclusion: Initial results suggest that airway epithelial cells in smokers acquire somatic mutations that gradually lead to malignant conversion. Deep sequencing replicate experiments are underway to expand these results. Citation Format: Daniel J. Craig, Thomas M. Blomquist, Erin L. Crawford, James C. Willey. Targeted deep sequencing of driver mutations in airway epithelial cells from smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3537.

Background: Genome-wide association studies (GWAS) and candidate gene studies suggest that telomere maintenance genes participate in etiology of lung cancer, idiopathic pulmonary fibrosis, and COPD. Telomeres are nucleoprotein structures located at the end of chromosomes that are maintained by telomerase encoded by hTERT. Telomerase is active in cancers, has the ability to aid in rapid cell division, and is dysfunctional in chronic conditions induced by inflammation as such as diabetes, renal failure, and COPD. hTERT is a known downstream target of β-catenin and WNT signaling. However, little is known regarding expression levels of these genes in normal bronchial epithelial cells (NBEC). The purpose of this study is to investigate inter-individual variation in regulation of β-catenin and WNT in NBEC, and if present, identify variants in regulatory region of human telomerase reverse transcriptase (hTERT) that could be used as candidate biomarkers for lung cancer risk. Methods: NBEC specimens from subjects with COPD (n=5) or without COPD (n=9) were obtained by bronchoscopy brush under IRB approved protocol. β-catenin, and WNT4 were measured by competitive multiplex-RT-PCR. Results: Both β-catenin and WNT4 displayed significant inter-individual variation as measured by Intra-Class Correlation (ICC) analysis (β-catenin ICC = 0.47, 95% Confidence Interval (0.2, 0.55), p < 0.05; WNT4 ICC = 0.60, 95% Confidence Interval (0.35, 0.85), p < 0.05). In patients with COPD, WNT4 expression was significantly higher in current smokers compared to former smokers (p Citation Format: Rose Zolondek, Daniel J. Craig, Erin L. Crawford, James C. Willey. Inter-individual variation in hTERT regulation pathway genes in normal bronchial epithelial cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1488.

The human genome is exposed to a variety of exogenous and endogenous assaults capable of inducing DNA damage and contributing to diseases like cancer. Multiple DNA repair mechanisms are tasked with identifying and repairing these aberrant nucleotides, but damage is occasionally missed giving rise to somatic mutations. As we age, the relative abundance of somatic mutations increases, which may increase our risk for developing cancer. In addition, inter-individual variation in somatic mutation prevalence suggests an inter-individual variation in (a) inherited DNA repair capacity and/or (b) exposure to environmental mutagens. Therefore, somatic mutation prevalence may serve as an end-point biomarker for cancer risk, as it provides critical information regarding both. While Next Generation Sequencing (NGS) has provided unparalleled access to the human genome and revolutionized the field of cancer genomics, its implementation into the clinical setting has been limited by technical errors introduced during library preparation and on the sequencing platform. This makes identification of rare variants below 10-4 mutations per nucleotide through NGS a challenge, and the use of somatic mutations to characterize cancer risk unfeasible. To address this issue, unique molecular indexes (UMI) were assigned to each genomic copy, enabling reliable identification of rare somatic mutations versus technical errors. We hypothesize that measurement of somatic mutation prevalence in normal bronchial epithelial cells (NBEC) will serve as an end-point biomarker for lung cancer risk by identifying both (a) inherited sub-optimal DNA repair/protection and (b) exposure to inhaled environmental mutagens including components of cigarette smoke, radon, and/or occupational hazards. In our initial pilot study, we used genomic DNA derived from an A549 cell line to optimize an ERCC5 gene-specific, dual-indexed PCR method for UMI assignment, followed by sequencing on the Illumina MiSeq platform. In parallel analyses, UMI correction using 25,000 genomic copies provided over 10-fold greater sensitivity in identifying somatic mutations compared to no UMI correction. Based on this pilot, we obtained three clinical NBEC specimens via cytology brush biopsy of grossly normal (non-cancerous) airway from (a) heavy smoker with lung cancer, (b) heavy smoker without lung cancer, and (c) non-smoking control. UMIs were assigned to 50,000 genomic copies at 16 loci, increasing our theoretical limit of detection to approximately 1 in 4x107 nucleotides. Results thus far support further application of this approach in studies to assess NBEC somatic mutation prevalence as a biomarker for cancer risk. Citation Format: Daniel J. Craig, Mazzin Elsamaloty, Thomas M. Blomquist, Erin L. Crawford, James C. Willey. Using rare variants to characterize lung cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2222.

Background. Based on increasing evidence from this laboratory and genome wide association studies (GWAS), single nucleotide polymorphisms (SNPs) responsible for inter-individual variation in normal bronchial epithelial cell (NBEC) cis-regulation of antioxidant, DNA repair, and cell cycle control genes are key determinants of lung cancer risk. Thus, there is a need for NBEC culture methods that enable extended population doublings without genetic alteration to enable experimental investigation of putative cis-regulatory SNPs in NBEC. Toward this goal, we assessed the effect of previously reported conditional reprogrammed culture (CRC) conditions on regulation of human telomerase reverse transcriptase (hTERT) transcript abundance and proliferative potential in NBEC. Methods. NBEC were obtained by bronchoscopic brush from eight individuals after obtaining informed consent to an IRB-approved protocol. NBEC were incubated in three different culture conditions: bronchial epithelial cell growth media (BEGM) only, co-cultured with irradiated mouse embryonic fibroblasts (IRR-MEF) + Rho kinase inhibitor (ROCKi) in BEGM, and conditioned BEGM + ROCKi. Media were changed every three days and cells were passaged and sub-cultured after ten days. Human telomerase reverse transcriptase (hTERT) was measured in three individuals after each passage in triplicate via qPCR. The proliferative capacity of all eight individuals was assessed using cell count and morphology at passage >3. Results. Co-culturing NBEC with IRR-MEF in BEGM supplemented with ROCKi produced a highly proliferative cell population while maintaining lineage commitment evident after removal of CRC conditions. Transcript abundance of hTERT was elevated 6.5-fold in NBEC in co-cultured conditions and 4.3-fold in NBEC in conditioned media compared to BEGM alone. Cell count in CRC conditions were up to 22-fold higher compared to BEGM alone. Cells were passaged and sub-cultured up to passage 4, followed by being frozen down in cell culture freezing media for further assessment. Conclusion. NBEC hTERT transcript abundance was up-regulated and cell population proliferative potential was extended in CRC conditions. It is likely that hTERT functions to protect the ends of linear chromosomes in dividing cells, enabling increased cell divisions while maintaining normal genome. These cell populations will be used in future studies to assess the effect of putative cis-regulatory single nucleotide polymorphisms (SNPs) on gene expression in NBEC. Citation Format: Daniel J. Craig, Rose T. Zolondek, Xiaolu Zhang, Jiyoun Yeo, Erin L. Crawford, James C. Willey. Induction of hTERT and increased proliferative potential in conditionally reprogrammed normal bronchial epithelial cells. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2905.