Abstract 204: Notch2NL is a novel regulator of radiation sensitivity in non-small cell lung cancer and a positive regulator of MYC activity

Abstract Background: A gain-of-function genetic screen identified NOTCH2 N-terminal like (NOTCH2NL) as a candidate novel gene involved in radiation resistance in non-small cell lung cancer (NSCLC). NOTCH2NL is located on chromosome position 1q21.1 which was incorrectly aligned in previous builds of the reference human genome sequence. NOTCH2NL was derived from a segmental duplication event in NOTCH2 during the evolutionary divergence between humans and non-human primates, forming three Notch2NL proteins: Notch2NL-A, Notch2NL-B and Notch2NL-C. Consequently, the only species whose genomes contain NOTCH2NL are modern and ancient humans. Notch2NL-B is a secreted protein and has been shown to promote Notch signalling in cortical stem cell progenitors via inhibition of inhibitory cis-DLL1/NOTCH signalling. Methods: Stable overexpression of NOTCH2NLB and secreted Notch2NL-B protein were validated by RT-qPCR and Western Blotting. The effects of NOTCH2NLB overexpression; transfer of Notch2NL-B protein from conditioned media onto wild-type cell lines; and siRNA knockdown of NOTCH1-4 transmembrane receptors on Notch signalling were quantified by a Notch luciferase reporter assay, RT-qPCR of classical NOTCH target genes and cancer stem cell marker (CSC) and RNA-Seq. Clonogenic cell survival assays determined the impact of NOTCH2NLB overexpression on radiation response. Cell proliferation was measured using the IncuCyte Zoom system. shRNA stable cell lines to knockdown NOTCH2NL were generated to mitigate the NOTCH2NLB overexpression phenotype we observed. RNA-Seq data from the first 100 patients from the TRACERx lung cancer study was used to quantify hallmark gene expression signatures and NOTCH2NLB expression. Results: NOTCH2NLB overexpression upregulates CSL-dependent Notch reporter luciferase activity; confers a radiation-resistant phenotype and impacts proliferation rate in NSCLC cell lines. Furthermore, we demonstrate that NOTCH2NLB overexpression and secreted Notch2NL-B protein transfer increase expression of classical NOTCH target genes (c-MYC, HES1 and HEY1) and CSC marker, ALDH1A1. Analysis of RNA-Seq data from the Lung TRACERx cohort study shows that NOTCH2NL is commonly expressed in NSCLC. NOTCH2NL expression positively correlates with notch hallmark gene expression signature in squamous (R=0.59, p=5.6e-9) and non-squamous carcinoma (R=0.51, p=4.7e-10). Interestingly, NOTCH2NL expression also positively correlated with the myc hallmark gene expression signature in squamous cell carcinoma (R=0.45, p=2.4e-5). Conclusions: Notch2NL is a novel determinant of radiation therapy response and impacts canonical Notch signalling in lung cancer. It is commonly expressed in NSCLC and can act in a paracrine manner as a secreted protein. Notch2NL, through canonical notch signalling, can regulate MYC expression and increase activity in the MYC pathway. Citation Format: Simranpreet Kaur Summan, Barbara Chow, Rhona Millar, Su Kit Chew, Philip East, Robert Hynds, Carlos Martinez Ruiz, Eva Gronroos, Mariam Jamal-Hanjani, Kevin Litchfield, Nicholas McGranahan, Nnennaya Kanu, Charles Swanton, Crispin Thomas Hiley. Notch2NL is a novel regulator of radiation sensitivity in non-small cell lung cancer and a positive regulator of MYC activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 204.</jats:p

Abstract 645: Heterogeneity of immunotherapy biomarkers in the TRACERx non-small cell lung cancer multi-region lung cancer cohort study

Abstract Immunotherapy containing regimens have become the standard of care first-line therapy for non-small cell lung cancer (NSCLC) in the metastatic setting and are being explored in the adjuvant and neo-adjuvant setting. However, as intratumor heterogeneity (ITH) is pervasive in cancer we investigated the impact of ITH on established and putative biomarkers predictive of immunotherapy response. We have used whole exome sequencing, RNA sequencing and PDL1 immunohistochemistry (IHC) derived from the multiregion treatment naïve TRACERx cohort to investigate this. Whole exome sequencing data was available for 432 primary tumours from 421 patients with greater than 1500 unique tumour regions. Tumour mutational burden (TMB) was calculated using best practice guidelines from the TMB harmonisation project. Using the FDA approved threshold of ≥ 10 mutations per megabase to define high TMB we found that 41% of patients with high TMB had at least one region with &amp;lt;10 mutation per megabase. This could result in misclassification of patients so we modelled increased sampling in this cohort and found that at least 5 spatially separated samples would be required to ensure no patients are misclassified. Contrary to the published literature we did not find TMB was confounded by tumour purity. Multi-region PDL1 IHC data using the FDA approved companion diagnostic assay (22c3) was available for 132 spatially separated tumour regions from 36 patients. Tumour regions were scored according to the established tumour proportion scoring system (≥50%, 49-1%, &amp;lt;1%). Using only a single sample 31% of patients would have been misclassified. Finally, we investigated several putative transcriptomic biomarkers including 10 single genes (e.g. CXCL9), 15 expression signatures (e.g cytolytic score, TIDE) and 2 tumour microenvironment classification systems. We found that 20-45% of these putative biomarkers were discordant when applied to multi-region data and this increased with the number of tumour regions per patients but was not impacted by tumour purity or sequencing depth. To investigate this further we compared the mean geneset RNA-ITH score between a geneset of all the immune biomarker genes with 100 randomly selected non-immune, but expressed, genesets. The immune biomarker gene set was subject to significantly more intra tumour heterogeneity of expression (Mean RNA-ITH Score 0.50 vs 0.31 p=6.4e-12). In conclusion we demonstrate significant heterogeneity of immune biomarkers in NSCLC and in particular a lack of robustness of expression-based predictors of response to immunotherapy. This highlights the need for biomarkers that are robust to intra-tumour heterogeneity and sampling bias or the need for more representative tumour sampling techniques. Citation Format: Crispin T. Hiley, Kevin Litchfield, Oriol Pich, David Moore, Cristina Naceur-Lombardelli, Selvaraju Veeriah, Maise Al Bakir, Simranpreet Summan, Kristiana Grigoriadis, Carlos Martinez Ruiz, Clare Puttick, Katey Enfield, Sophia Ward, Alexander Frankell, Dhruva Biswas, Rachel Rosenthal, Nicolai J. Birkbak, Mariam Jamal-Hanjani, Nicholas McGranahan, Charles Swanton, TRACERx Consortium. Heterogeneity of immunotherapy biomarkers in the TRACERx non-small cell lung cancer multi-region lung cancer cohort study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 645.</jats:p

Representative sequencing: Unbiased sampling of solid tumor tissue

International audienceAlthough thousands of solid tumors have been sequenced to date, a fundamental under-sampling bias isinherent in current methodologies. This is caused by a tissue sample input of fixed dimensions (e.g., 6 mmbiopsy), which becomes grossly under-powered as tumor volume scales. Here, we demonstrate representative sequencing (Rep-Seq) as a new method to achieve unbiased tumor tissue sampling. Rep-Seq uses fixed residual tumor material, which is homogenized and subjected to next-generation sequencing. Analysis of intratumor tumor mutation burden (TMB) variability shows a high level of misclassification using current single-biopsy methods, with 20% of lung and 52% of bladder tumors having at least one biopsy with high TMB butlow clonal TMB overall. Misclassification rates by contrast are reduced to 2% (lung) and 4% (bladder) when a more representative sampling methodology is used. Rep-Seq offers an improved sampling protocol for tumor profiling, with significant potential for improved clinical utility and more accurate deconvolution of clonal structure