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209 Background: Metastatic colorectal (CRC), pancreatic (PANC), and gastroesophageal cancers are the leading causes of GI cancer–related mortality (5-y survival: 15%, 3%, and 5%-6%, respectively) (ACS 2022). HLA LOH is a recurrent mechanism of immune escape observed in 15%-20% of GI cancers (Hecht R., ASCO GI 2022). The Tmod platform is a logic-gated chimeric antigen receptor (CAR) T-cell modular system, comprising a carcinoembryonic antigen (CEA)- or mesothelin (MSLN)-targeting CAR activator and a separate HLA-A*02-targeting blocker receptor. Both in vitro/in vivo, Tmod CAR T therapy kills cells with HLA-A*02 LOH (tumor) without harming cells with retained HLA-A*02 expression (normal). However, HLA-A*02 LOH can only be therapeutically exploited if patients are identifiable through a feasible and timely clinical workflow. Methods: We established a biobanking protocol (BASECAMP-1, NCT04981119) to determine whether HLA-A*02 LOH patients can be prospectively identified. Patients with CRC, PANC, or non-small cell lung cancer (NSCLC), and a high risk for incurable relapse, were screened first using a standard HLA assay. Heterozygous HLA-A*02 positive tumor samples were then assessed for LOH using a bioinformatic algorithm applied via the Tempus xT platform. Results: As of Sep 1, 2022, 83 patients were consented at 4 institutions. HLA status was obtained from 70 patients and 28 were identified as HLA-A*02:01 heterozygous (40%; expected frequency based on USA NMDP data, 27.6%). LOH results were available for 16 patients; 4 LOH-positive patients were identified (25%, 2 PANC, 2 NSCLC). The LOH assay sensitivity declines below a tumor purity of 40% (Hecht R., ASCO GI 2022). Six patients had a tumor purity of 20% (all with PANC, a tumor known for high stromal content), limiting possible LOH detection. The impact of tumor purity on LOH sensitivity was highlighted in a patient with a low initial sample tumor purity (30%) that resulted in a 41% probability of HLA-A*02:01 LOH (below positive threshold). A second sample with a higher tumor purity (70%), obtained from formalin-fixed, paraffin-embedded sections, resulted in a 92% probability of HLA-A*02:01 LOH (positive). Conclusions: BASECAMP-1 prospective identification of HLA-A*02 LOH is feasible in the real-world setting. The frequencies of the HLA-A*02 allele and of HLA-A*02 LOH in this cohort mirrored expected population frequencies. LOH results can be obtained within a clinically feasible workflow and timeframe, although samples with a < 40% tumor purity have a reduced sensitivity for LOH detection, an issue recurrently observed in patients with PANC. The BASECAMP-1 strategy enables prospective identification of appropriate patients for future therapeutic clinical trials using Tmod CEA and MSLN logic-gated CAR T cells. Clinical trial information: NCT04981119 .

Genomic analysis of paired tumor–normal samples and clinical data can be used to match patients to cancer therapies or clinical trials. We analyzed 500 patient samples across diverse tumor types using the Tempus xT platform by DNA-seq, RNA-seq and immunological biomarkers. The use of a tumor and germline dataset led to substantial improvements in mutation identification and a reduction in false-positive rates. RNA-seq enhanced gene fusion detection and cancer type classifications. With DNA-seq alone, 29.6% of patients matched to precision therapies supported by high levels of evidence or by well-powered studies. This proportion increased to 43.4% with the addition of RNA-seq and immunotherapy biomarker results. Combining these data with clinical criteria, 76.8% of patients were matched to at least one relevant clinical trial on the basis of biomarkers measured by the xT assay. These results indicate that extensive molecular profiling combined with clinical data identifies personalized therapies and clinical trials for a large proportion of patients with cancer and that paired tumor–normal plus transcriptome sequencing outperforms tumor-only DNA panel testing. Genomic profiling of cancer samples yields more therapeutic options by including germline, RNA-seq and immunotherapy biomarkers.

Liquid biopsy is a valuable precision oncology tool that is increasingly used as a non-invasive approach to identify biomarkers, detect resistance mutations, monitor disease burden, and identify early recurrence. The Tempus xF liquid biopsy assay is a 105-gene, hybrid-capture, next-generation sequencing (NGS) assay that detects single-nucleotide variants, insertions/deletions, copy number variants, and chromosomal rearrangements. Here, we present extensive validation studies of the xF assay using reference standards, cell lines, and patient samples that establish high sensitivity, specificity, and accuracy in variant detection. The Tempus xF assay is highly concordant with orthogonal methods, including ddPCR, tumor tissue-based NGS assays, and another commercial plasma-based NGS assay. Using matched samples, we developed a dynamic filtering method to account for germline mutations and clonal hematopoiesis, while significantly decreasing the number of false-positive variants reported. Additionally, we calculated accurate circulating tumor fraction estimates (ctFEs) using the Off-Target Tumor Estimation Routine (OTTER) algorithm for targeted-panel sequencing. In a cohort of 1,000 randomly selected cancer patients who underwent xF testing, we found that ctFEs correlated with disease burden and clinical outcomes. These results highlight the potential of serial testing to monitor treatment efficacy and disease course, providing strong support for incorporating liquid biopsy in the management of patients with advanced disease.

TPS2676 Background: Solid tumors comprise > 90% of cancers. Metastatic colorectal cancer, non-small cell lung cancer, and pancreatic cancer are among the leading causes of cancer-related mortality (5-year overall survival: 14%, 6%, and 3%, respectively) (ACS. 2021). Chimeric antigen receptor (CAR) T-cell therapy has demonstrated clinical efficacy in hematologic malignancies (Neelapu S. et al. N Engl J Med. 2017). Translating engineered T-cell therapies to solid tumors has proven to be challenging due to a lack of tumor-specific targets that can discriminate cancer cells from normal cells. Previous studies using carcinoembryonic antigen (CEA) T-cell receptors and mesothelin (MSLN) CARs resulted in dose-limiting on-target, off-tumor toxicities (Parkhurst M, et al. Mol Ther. 2011; Tanyi J. Cellicon Valley '21). To create a therapeutic safety window, Tmod CAR T-cell therapy utilizes dual-signaling receptors to create a robust NOT logic gate capable of killing tumor cells, while leaving healthy cells intact (Hamburger A, et al. Mol Immunol. 2020). The 2 receptors in Tmod CAR T-cell therapy comprise an activator that recognizes an antigen on the surface of tumor cells that may also be present on normal cells, such as CEA and MSLN, and a blocker that recognizes a second surface antigen from an allele lost only in tumor cells. The frequency of HLA LOH among advanced GI solid tumor cancers in the Tempus real-world dataset is 16.3% with a range of 15.6%-20.8% between colorectal, pancreatic, and gastroesophageal tumors (Hecht R. et al. ASCO-GI 2022. Abstract #190). As such, HLA LOH offers a definitive tumor versus normal discriminator target for CAR T-cell therapy. Different activator/blocker combinations can be engineered with the Tmod platform technology and may be applied to T cells and natural killer cells in autologous and allogeneic settings. BASECAMP-1 is a currently enrolling observational study with key objectives of 1) To identify patients with somatic HLA LOH eligible for Tmod CAR T-cell therapy, and 2) To obtain leukapheresis and feasibility for the future EVEREST Tmod CAR T-cell trial. Methods: BASECAMP-1 (NCT04981119) patient eligibility has 2 parts: 1) Patients will be initially screened to identify germline HLA-A*02 heterozygosity by central NGS. If HLA-A*02 heterozygosity is confirmed, primary archival tumor tissue will be analyzed for somatic mutations by xT-Onco NGS testing. 2) If the tumor demonstrates HLA-A*02 LOH and the patient is eligible after screening, the patient will undergo leukapheresis. Banked T cells will be available for the autologous EVEREST Tmod CAR T-cell therapy interventional study to reduce waiting time at relapse. Clinical trial information: NCT04981119.

190 Background: Metastatic colorectal (CRC), pancreatic (PANC), and gastroesophageal (GE) cancers are the leading causes of GI cancer–related mortality (5-yr survival rate, 14%, 3% and ̃5-6%, respectively). T-cell immunotherapy targeting GI-associated tumor antigens has been attempted, but efficacy has been constrained by on-target off-tumor toxicity, limiting the therapeutic window. The Tmod (TM) platform is an AND-NOT logic-gated CAR T modular system, versions of which have a CEA- or MSLN-targeting CAR activator and a separate HLA-A*02-targeting blocker receptor to protect normal cells. Tmod CAR T exploits HLA LOH, common in GI malignancies (10-33% in primary solid tumors [TCGA]) and can kill tumor cells without harming healthy cells in vitro and in vivo. However, the prevalence of HLA LOH across GI tumors is unknown in the real-world setting. We utilized the Tempus xT oncology NGS database of patients with multiple GI tumors. From a standard-of-care NGS assay, GI cancer patients can be readily identified for HLA LOH and future treatment with Tmod CAR T therapy. Methods: The occurrence of HLA LOH in GI tumors of 1439 patients was assessed using paired germline and somatic DNA sequencing using a research assay [6]. CRC, PANC and GE patients with ≥ stage 3 were then extracted, and rates of HLA LOH were identified (ie, whether loss occurred across high-frequency HLA-A alleles). In addition, mutations in KRAS and BRAF, as well as MSI status were stratified to determine any association with HLA-A LOH. Results: HLA-A LOH was detected in 830 (17.3%) of all solid tumor records, and a similar proportion when all GI cancer records were analyzed (17.0%). For GI subtypes, these values ranged from 13.5% to 23.1% (Table). No high-frequency HLA-A allele (A*01, A*02, A*03, A*11) was more likely to be lost. Clinical biomarkers ( KRAS, BRAF and MSI status) were not associated with HLA-LOH. Conclusions: The frequency of HLA LOH among advanced solid tumor cancers in this dataset is 17.3%, with a range of 13.5-23% between CRC, PANC and GE. The HLA LOH frequency observed in these GI tumors is consistent with that in primary tumors from TCGA, which also used germline-matched and tumor samples. Clinical biomarkers were not associated with HLA LOH. Tempus NGS was able to identify HLA LOH, which can be used for Tmod CAR T therapy to an enhanced therapeutic window. Identification of these patients in BASECAMP-1 (NCT04981119) will enable novel Tmod CAR T therapy. [Table: see text]

BackgroundSolid tumors comprise >90% of cancers. Metastatic colorectal cancer, non-small cell lung cancer, and pancreatic cancer are among the leading causes of cancer-related mortality (5-year overall survival: 14%, 6%, and 3%, respectively).1Chimeric antigen receptor (CAR) T-cell therapy demonstrated clinical outcomes in hematologic malignancies.2 3 However, translating engineered T-cell therapies to solid tumors proves difficult due to a lack of tumor-specific targets that discriminate cancer cells from normal cells. In previous studies, the use of a carcinoembryonic antigen T-cell receptors and mesothelin CARs both resulted in dose-limiting on-target, off-tumor toxicities.4 5 TmodTM CAR T-cell therapy addresses these challenges by leveraging dual receptors to create a robust AND NOT signal integrator capable of killing tumor cells, while leaving healthy cells intact (figure 1).6 Tmod platform technology is a versatile system that may be applied to T cells and natural killer cells in autologous and allogeneic settings.HLA LOH offers a definitive tumor versus normal discriminator target for CAR T-cell therapy.6 7 The 2 receptors comprise an activator that recognizes an antigen present on the surface of normal and tumor cells and a blocker that recognizes a second surface antigen from an allele lost only in tumor cells. HLA LOH has been observed in ~13% across all solid tumors and up to 33% of pancreatic cancers.8 New technologies have shown higher HLA LOH rates; however, it is unclear whether patients with HLA LOH in their primary tumor tissues are at higher risk for recurrence. BASECAMP-1 is an observational study with key objectives: 1) To determine and identify patients with somatic HLA LOH eligible for Tmod CAR T-cell therapy, and 2) Subsequent leukapheresis and manufacturing feasibility for future Tmod CAR T-cell trials.MethodsBASECAMP-1 (NCT04981119) patient eligibility has 2 parts (figure 2): 1) Patients will be initially screened to identify germline HLA-A*02 heterozygosity by central next-generation sequencing (NGS). If HLA-A*02 heterozygosity is confirmed, primary archival tumor tissue will be analyzed by xT-Onco NGS testing9 to determine if somatic tumor HLA-A*02 LOH is present; 2) If the tumor demonstrates HLA-A*02 LOH and the patient screens eligible, the patient will undergo leukapheresis. Patients enrolled in the study who undergo leukapheresis will be evaluated for safety 7 days post-leukapheresis and followed for relapsed status. Banked T cells will be available for subsequent autologous Tmod CAR T-cell therapy at the time of relapse.Abstract 491 Figure 1Illustration of the Tmod T cell engaging with tumor cells with somatic loss of HLA-A*02 and with normal cellsAbstract 491 Figure 2Study schema. HLA, human leukocyte antigen; LOH, loss of heterozygosity; NGS, next generation sequencingTrial RegistrationNCT04981119ReferencesAmerican Cancer Society. Cancer Facts & Figures 2021. Atlanta: American Cancer Society; 2021.Neelapu S, Locke F, Bartlett N, et al. Axicabtagene ciloleucel CAR T-cell therapy in refractory large B-cell lymphoma. N Engl J Med 2017;377(26):2531–2544.Maude S, Laetsch T, Buechner J, et al. Tisagenlecleucel in children and young adults with B-cell lymphoblastic leukemia. N Engl J Med 2018;378(5):439–448.Parkhurst M, Yang J, Langan R, et al. T cells targeting carcinoembryonic antigen can mediate regression of metastatic colorectal cancer but induce severe transient colitis. Mol Ther 2011;19(3):620–626.Haas AR, Tanyi JL, O’Hara MH, et al. Phase I study of lentiviral-transduced chimeric antigen receptor-modified T cells recognizing mesothelin in advanced solid cancers. Mol Ther. 2019;27(11):1919–1929.Hamburger A, DiAndreth B, Cui J, et al. Engineered T cells directed at tumors with defined allelic loss. Mol Immunol 2020;128:298–310.Hwang M, Mog B, Douglass J, et al. Targeting loss of heterozygosity for cancer-specific immunotherapy. Proc Natl Acad Sci U S A 2021;118(12):e2022410118.The Cancer Genome Atlas (TCGA) Research Network. https://www.cancer.gov/tcga. Accessed June 2021.Perera J, Mapes B, Lau D, et al. Detection of human leukocyte antigen class I loss of heterozygosity in solid tumor types by next-generation DNA sequencing. J Immunother Cancer 2019;7(suppl 1):103.

Background: Oncogenic cancers, such as human papillomavirus (HPV) and Epstein Barr virus (EBV), account for 10 to 12% of all cancers. Knowing the viral status of a tumor is essential as it may change patients’ treatment options. Numerous clinical trials investigating the benefit of radiation or chemotherapy dose reduction for HPV positive head and neck cancers have shown promising results. Additionally, virus-associated tumors are more likely to present higher levels of inflammation and immune infiltration, which make them good candidates for immunotherapy. We developed a novel viral detection algorithm using the patient’s tumor whole transcriptome profiles to predict viral status. As RNA-sequencing of clinical samples becomes increasingly common, the use of gene expression data for viral status and insights about the tumor immune microenvironment may impact clinical treatment decisions for a larger number of patients. Methods: To develop RNA based classifiers of viral status from tumor transcriptomes, we used the TCGA cervical cancer, head and neck cancer, and gastric cancer cohorts with known viral statuses. To identify predictive genes, we performed a 10-fold cross validation on the TCGA cohorts and trained a Logistic Regression with a L1 regularisation. Since L1 regularization leads to sparse coefficients, only a small subset of genes had non-zero coefficients at each split. Only the genes with non-zero coefficients in more than 80% of the splits were included in the final model. Using this subset of genes, we again trained Logistic Regression classifiers with a L1 regularisation on the TCGA dataset and validated our models on Tempus cohorts. Results: Our model can predict the HPV subtype with a 99% specificity and 99% sensitivity, and the EBV subtype with a 99% specificity and 100% sensitivity in the TCGA cohorts. In our Tempus validation cohorts, we report 96% specificity and a 88% sensitivity for HPV, and a 97% specificity and a 100% sensitivity for EBV. Subsequent analysis of whole transcriptome data showed a significant increase of the interferon gamma signature, the cytolytic index and the immunotherapy target IDO1 in EBV positive patients in both cohorts. We observed the same pattern in the HPV cohorts, though the increase was not significant in the Tempus cohorts due to the small sample size. Conclusions: Our models accurately predicts viral infection in tumors using RNA expression data. We confirm viral infections are generally associated with an upregulation of immune responses. Viral detection based on whole transcriptome data could become a useful clinical tool in combination with existing methods, providing insights about the viral status and tumor microenvironment with one test. Citation Format: Ariane Lozac’hmeur, Denise Lau, Aly Khan. Predicting oncogenic viral status using RNA signatures [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 135.