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Purpose: The Piedmont study is a prospectively designed retrospective evaluation of a new 48-gene antifolate response signature (AF-PRS) in patients with locally advanced/metastatic NS-NSCLC treated with pemetrexed-containing platinum doublet chemotherapy (PMX-PDC). The study tested the hypothesis that AF-PRS selects for patients with NS-NSCLC that preferentially respond to PMX-PDC, with a goal of providing clinical support for AF-PRS as potential diagnostic test. Experimental Design: Residual pre-treatment FFPE tumor samples and clinical data were analyzed from 105 patients treated with 1st-line (1L) PMX-PDC. 95 patients had sufficient RNA sequencing (RNAseq) data quality and clinical annotation for inclusion in the analysis. Associations between AF-PRS status and associate genes, and outcome measures including progression-free survival (PFS) and clinical response were evaluated. Results: Overall, 53% of patients were AF-PRS(+), which was associated with extended PFS, but not OS, vs. AF-PRS(-) (16.6 vs. 6.6 mo; p = 0.025). In patients who were Stage I-III patients at time of treatment, PFS was further extended in AF-PRS(+) vs. AF-PRS(-) (36.2 vs. 9.3 mo; p = 0.03). Complete response (CR) to therapy was noted in 14 of 95 patients. AF-PRS(+) preferentially selected a majority (79%) of CRs, which were evenly split between patients Stage I-III (6 of 7) and Stage IV (5 of 7) at time of treatment. Conclusions: AF-PRS identified a significant population of patients with extended PFS and/or clinical response following PMX-PDC treatment. AF-PRS may be a useful diagnostic test for patients indicated for systemic chemotherapy, especially when determining the optimal PDC regimen for locally advanced disease.

As an aneuploidy, trisomy is associated with mammalian embryonic and postnatal abnormalities. Understanding the underlying mechanisms involved in mutant phenotypes is broadly important and may lead to new strategies to treat clinical manifestations in individuals with trisomies, such as trisomy 21 [Down syndrome (DS)]. Although increased gene dosage effects because of a trisomy may account for the mutant phenotypes, there is also the possibility that phenotypic consequences of a trisomy can arise because of the presence of a freely segregating extra chromosome with its own centromere, i.e. a ‘free trisomy’ independent of gene dosage effects. Presently, there are no reports of attempts to functionally separate these two types of effects in mammals. To fill this gap, here we describe a strategy that employed two new mouse models of DS, Ts65Dn;Df(17)2Yey/+ and Dp(16)1Yey/Df(16)8Yey. Both models carry triplications of the same 103 human chromosome 21 gene orthologs; however, only Ts65Dn;Df(17)2Yey/+ mice carry a free trisomy. Comparison of these models revealed the gene dosage-independent impacts of an extra chromosome at the phenotypic and molecular levels for the first time. They are reflected by impairments of Ts65Dn;Df(17)2Yey/+ males in T-maze tests when compared with Dp(16)1Yey/Df(16)8Yey males. Results from the transcriptomic analysis suggest the extra chromosome plays a major role in trisomy-associated expression alterations of disomic genes beyond gene dosage effects. This model system can now be used to deepen our mechanistic understanding of this common human aneuploidy and obtain new insights into the effects of free trisomies in other human diseases such as cancers.

Purpose: The high prevalence of osteoblastic bone metastases in prostate cancer involves the production of osteoblast-stimulating factors by prostate cancer cells. Prostate-specific antigen (PSA) is a serine protease uniquely produced by prostate cancer cells and is an important serologic marker for prostate cancer. In this study, we examined the role of PSA in the induction of osteoblast differentiation.Experimental Design: Human cDNA containing a coding region for PSA was transfected into human osteosarcoma SaOS-2 cells. SaOS-2 cells were also treated with exogenously added PSA. We evaluated changes in global gene expression using cDNA arrays and Northern blot analysis resulting from expression of PSA in human osteosarcoma SaOS-2 cells.Results: SaOS-2 cells expressing PSA had markedly up-regulated expression of genes associated with osteoblast differentiation including runx-2 and osteocalcin compared with the controls. Consistent with these results, the stable clones expressing PSA showed increased mineralization and increased activity of alkaline phosphatase in vitro compared with controls, suggesting that these cells undergo osteoblast differentiation. We also found that osteoprotegerin expression was down-regulated and that the receptor activator of NF-κB ligand expression was up-regulated in cells expressing PSA compared with controls.Conclusions: Modulation of the expression of osteogenic genes and alteration of the balance between osteoprotegerin–receptor activator of NF-κB ligand by PSA suggests that PSA produced by metastatic prostate cancer cells may participate in bone remodeling in favor of the development of osteoblastic metastases in the heterogeneous mixture of osteolytic and osteoblastic lesions. These findings provide a molecular basis for understanding the high prevalence of osteoblastic bone metastases in prostate cancer.

Supplementary tables 1s-4s. Supplementary Table 1s. Concordance of variant calls. Supplementary Table 2s. Breast cancer-related genes from the Cancer Gene Consensus database. Supplementary Table 3s. Concordance of variant calls in known breast cancer genes. Supplementary Table 4s. Discordant variant calls in breast cancer-related genes.

Background: Whole-exome sequencing (WES) has recently emerged as an appealing approach to systematically study coding variants. However, the requirement for a large amount of high-quality DNA poses a barrier that may limit its application in large cancer epidemiologic studies. We evaluated the performance of WES with low input amount and saliva DNA as an alternative source material.Methods: Five breast cancer patients were randomly selected from the Pathways Study. From each patient, four samples, including 3 μg, 1 μg, and 0.2 μg blood DNA and 1 μg saliva DNA, were aliquoted for library preparation using the Agilent SureSelect Kit and sequencing using Illumina HiSeq2500. Quality metrics of sequencing and variant calling, as well as concordance of variant calls from the whole exome and 21 known breast cancer genes, were assessed by input amount and DNA source.Results: There was little difference by input amount or DNA source on the quality of sequencing and variant calling. The concordance rate was about 98% for single-nucleotide variant calls and 83% to 86% for short insertion/deletion calls. For the 21 known breast cancer genes, WES based on low input amount and saliva DNA identified the same set variants in samples from a same patient.Conclusions: Low DNA input amount, as well as saliva DNA, can be used to generate WES data of satisfactory quality.Impact: Our findings support the expansion of WES applications in cancer epidemiologic studies where only low DNA amount or saliva samples are available. Cancer Epidemiol Biomarkers Prev; 24(8); 1207–13. ©2015 AACR.

Supplementary Table 1 from Prostate-Specific Antigen Modulates Genes Involved in Bone Remodeling and Induces Osteoblast Differentiation of Human Osteosarcoma Cell Line SaOS-2

Supplementary Figure 2s. Comparisons of quality metrics between concordant and discordant short insertion/deletions (indel).

Supplementary Figure 1s. Comparisons of quality metrics between concordant and discordant single nucleotide variants (SNVs).

Background Tumor mutational burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability can help facilitate comparability across different panel assays, which may aid in broader adoption of panel assays and development of clinical applications. Materials and methods Twenty-nine tumor samples and 10 human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values. Results Panel sizes >667 Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cut-offs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from The Cancer Genome Atlas data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples. Conclusions Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available.

Introduction Although obesity is associated with adverse cancer outcomes in general, most retrospective clinical studies suggest a beneficial effect of obesity in NSCLC. Methods Hypothesizing that this “obesity paradox” arises partly from the limitations of using body mass index (BMI) to measure obesity, we quantified adiposity using preoperative computed tomography images. This allowed the specific determination of central obesity as abdominal visceral fat area normalized to total fat area (visceral fat index [VFI]). In addition, owing to the previously reported salutary effect of metformin on high-BMI patients with lung cancer, metformin users were excluded. We then explored associations between visceral obesity and outcomes after surgical resection of stage I and II NSCLC. We also explored potential immunologic underpinnings of such association using complimentary analyses of tumor gene expression data from NSCLC tumors and the tumor transcriptome and immune microenvironment in an immunocompetent model of lung cancer with diet-induced obesity. Results We found that in 513 patients with stage I and II NSCLC undergoing lobectomy, a high VFI is associated with decreased recurrence-free and overall survival. VFI was also inversely related to an inflammatory transcriptomic signature in NSCLC tumors, consistent with observations made in immunocompetent murine models wherein diet-induced obesity promoted cancer progression while exacerbating elements of immune suppression in the tumor niche. Conclusions In all, this study uses multiple lines of evidence to reveal the adverse effects of visceral obesity in patients with NSCLC, which align with those found in animal models. Thus, the obesity paradox may, at least in part, be secondary to the use of BMI as a measure of obesity and the confounding effects of metformin use.

Background Contemporary to the rapidly evolving landscape of cancer immunotherapy is the equally changing understanding of immune tumor microenvironments (TMEs) which is crucial to the success of these therapies. Their reliance on a robust host immune response necessitates clinical grade measurements of immune TMEs at diagnosis. In this study, we describe a stable tumor immunogenic profile describing immune TMEs in multiple tumor types with ability to predict clinical benefit from immune checkpoint inhibitors (ICIs). Methods A tumor immunogenic signature (TIGS) was derived from targeted RNA-sequencing (RNA-seq) and gene expression analysis of 1323 clinical solid tumor cases spanning 35 histologies using unsupervised analysis. TIGS correlation with ICI response and survival was assessed in a retrospective cohort of NSCLC, melanoma and RCC tumor blocks, alone and combined with TMB, PD-L1 IHC and cell proliferation biomarkers. Results Unsupervised clustering of RNA-seq profiles uncovered a 161 gene signature where T cell and B cell activation, IFNg, chemokine, cytokine and interleukin pathways are over-represented. Mean expression of these genes produced three distinct TIGS score categories: strong (n = 384/1323; 29.02%), moderate (n = 354/1323; 26.76%), and weak (n = 585/1323; 44.22%). Strong TIGS tumors presented an improved ICI response rate of 37% (30/81); with highest response rate advantage occurring in NSCLC (ORR = 36.6%; 16/44; p = 0.051). Similarly, overall survival for strong TIGS tumors trended upward (median = 25 months; p = 0.19). Integrating the TIGS score categories with neoplastic influence quantified via cell proliferation showed highly proliferative and strong TIGS tumors correlate with significantly higher ICI ORR than poorly proliferative and weak TIGS tumors [14.28%; p = 0.0006]. Importantly, we noted that strong TIGS and highly [median = not achieved; p = 0.025] or moderately [median = 16.2 months; p = 0.025] proliferative tumors had significantly better survival compared to weak TIGS, highly proliferative tumors [median = 7.03 months]. Importantly, TIGS discriminates subpopulations of potential ICI responders that were considered negative for response by TMB and PD-L1. Conclusions TIGS is a comprehensive and informative measurement of immune TME that effectively characterizes host immune response to ICIs in multiple tumors. The results indicate that when combined with PD-L1, TMB and cell proliferation, TIGS provides greater context of both immune and neoplastic influences on the TME for implementation into clinical practice.

Strategies for unlocking immunosuppression in the tumor microenvironment have been investigated to overcome resistance to first-generation immune checkpoint blockade with anti- programmed cell death protein 1 (PD-1)/ programmed death-ligand 1 (PD-L1) and anti-cytotoxic T-lymphocyte associated protein 4 (CTLA-4) agents. Indoleamine 2,3-dioxygenase (IDO) 1, an enzyme catabolizing tryptophan to kynurenine, creates an immunosuppressive environment in preclinical studies. Early phase clinical trials investigating inhibition of IDO1, especially together with checkpoint blockade, provided promising results. Unfortunately, the phase 3 trial of the IDO1 inhibitor epacadostat combined with the PD-1 inhibitor pembrolizumab did not show clinical benefit when compared with pembrolizumab monotherapy in patients with advanced malignant melanoma, which dampened enthusiasm for IDO inhibitors. Even so, several molecules, such as the aryl hydrocarbon receptor and tryptophan 2,3-dioxygenase, were reported as additional potential targets for the modulation of the tryptophan pathway, which might enhance clinical effectiveness. Furthermore, the combination of IDO pathway blockade with agents inhibiting other signals, such as those generated by PIK3CA mutations that may accompany IDO1 upregulation, may be a novel way to enhance activity. Importantly, IDO1 expression level varies by tumor type and among patients with the same tumor type, suggesting that patient selection based on expression levels of IDO1 may be warranted in clinical trials.

Background: Homologous recombination deficiency (HRD), broadly defined as a loss of the cellular mechanism underlying homologous recombination, is often observed in breast cancer. HRD causes distinctive perturbations to tumor genomic architecture that allow for its molecular identification, while also rendering HRD+ cancers vulnerable to specific chemotherapeutic interventions. This makes the molecular identification of HRD a promising avenue in precision medicine of breast cancer. Specific features of HRD include the presence of large-scale transitions (LST), telomeric allelic imbalance (TAI) and Loss of Heterozygosity (LOH). Each are readily detectable via targeted next generation sequencing (tNGS) or via array-based genotyping. However, genome-wide approaches for HRD detection using cost-effective methods, such as low-pass sequencing (LP-WGS), remain relatively under-explored. Here, we investigated whether HRD signals can be successfully re-capitulated using LP-WGS technology and benchmarked our results against the current field standard (both tNGS and array genotyping). Methods: LP-WGS and tNGS was performed on 96 samples across a range of tumor types (including N=17 breast cancer samples). LP-WGS libraries were prepared using Nextera (Illumina) using 0.4ng DNA input, and sequenced to 0.5-1x coverage. tNGS libraries were prepared using TSO500 (Illumina) using 40-80ng input, and sequenced to >150x unique read coverage. Regions of CNV were estimated using CNVKit v0.9.6, and regions of LOH were estimated using a novel ancestry-aware method. Small variant detection was performed using the TSO500 v2.2.0.12 analysis pipeline. SNP array analysis of 12 tumor samples using Oncoscan (ThermoFisher) was also performed. CNV and LOH estimates derived from LP-WGS, TSO500 and SNP array data were calculated using Jaccard similarity, treating the SNP array data as the “ground truth”. Results: We benchmarked HRD signals derived from LP-WGS compared to the array-based calls and observed near perfect sensitivity for CNV gains across samples (Jaccard index=1.0), as well as for CNV losses between LP-WGS and SNP array (Jaccard index=1.0). We additionally noted that LPS-WGS calls captured both CNV loss and gains that were not detectable via the SNP array. For TAI, LP-WGS re-capitulated 7/10 unique signals also identified via array. We also observed high concordance between regions of the genome called LOH between both platforms (median Jaccard index=0.70, IQR=0.254), but noted an attenuation of sensitivity in samples where estimated tumor heterogeneity was high. We also evaluated LP-WGS CNV calls against the TSO500 assay and noted high sensitivity (96%; 94%) and specificity (89%; 91%) for both CNV gains and losses, respectively. Conclusions: Workflows incorporating LP-WGS can support the detection of HRD genome-wide, paving the way for a more affordable assay that may help to inform clinical decision making in the future treatment of breast cancer. Citation Format: Gillian Belbin, Jie An, Chase Mazur, Joseph Pickrell, Jeremy Li, Daniel Metzger, Shuang Gao, Erik Van Roey, Robert Seager, Sarabjot Pabla, Durga Prasad Dash, Jeffrey M. Conroy. Application of low-pass whole genome sequencing for the detection of Homologous Recombination Deficiency in breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-02-54.

Recent epidemiological studies have shown that obesity, typically measured by increased body mass index (BMI), is associated with an increased risk of gastroesophageal adenocarcinoma (GEAC), but the contributing molecular and immune mechanisms remain unknown. Since obesity is known to promote chronic inflammation, we hypothesized that obesity leads to inflammation-related immune dysfunction, which can be reversed by immune-modulating therapy. To test our hypothesis, we examined the clinical and molecular data from advanced GEAC patients. To this end, 46 GEAC tumors were evaluated for biomarkers representing tumor inflammation, cell proliferation, and PD-L1 expression. A CoxPH regression model with potential co-variates, followed by pairwise post hoc analysis, revealed that inflammation in the GEAC tumor microenvironment is associated with improved overall survival, regardless of BMI. We also observed a significant association between cell proliferation and progression-free survival in overweight individuals who received immune-modulating therapy. In conclusion, our data confirm the role of the immune system in the natural course of GEAC and its responses to immunotherapies, but do not support the role of BMI as an independent clinically relevant biomarker in this group of patients.

BackgroundImmune checkpoint inhibitor-based therapies have achieved impressive success in the treatment of several cancer types. Predictive immune biomarkers, including PD-L1, MSI and TMB are well established as surrogate markers for immune evasion and tumor-specific neoantigens across many tumors. Positive detection across cancer types varies, but overall ~50% of patients test negative for these primary immune markers.1 In this study, we investigated the prevalence of secondary immune biomarkers outside of PD-L1, TMB and MSI.MethodsComprehensive genomic and immune profiling, including PD-L1 IHC, TMB, MSI and gene expression of 395 immune related genes was performed on 6078 FFPE tumors representing 34 cancer types, predominantly composed of lung cancer (36.7%), colorectal cancer (11.9%) and breast cancer (8.5%). Expression levels by RNA-seq of 36 genes targeted by immunotherapies in solid tumor clinical trials, identified as secondary immune biomarkers, were ranked against a reference population. Genes with a rank value ≥75th percentile were considered high and values were associated with PD-L1 (positive ≥1%), MSI (MSI-H or MSS) and TMB (high ≥10 Mut/Mb) status. Additionally, secondary immune biomarker status was segmented by tumor type and cancer immune cycle roles.ResultsIn total, 41.0% of cases were PD-L1+, 6.4% TMB+, and 0.1% MSI-H. 12.6% of cases were positive for >2 of these markers while 39.9% were triple negative (PD-L1-/TMB-/MSS). Of the PD-L1-/TMB-/MSS cases, 89.1% were high for at least one secondary immune biomarker, with 69.3% having ≥3 markers. PD-L1-/TMB-/MSS tumor types with ≥50% prevalence of high secondary immune biomarkers included brain, prostate, kidney, sarcoma, gallbladder, breast, colorectal, and liver cancer. High expression of cancer testis antigen secondary immune biomarkers (e.g., NY-ESO-1, LAGE-1A, MAGE-A4) was most commonly observed in bladder, ovarian, sarcoma, liver, and prostate cancer (≥15%). Tumors demonstrating T-cell priming (e.g., CD40, OX40, CD137), trafficking (e.g., TGFB1, TLR9, TNF) and/or recognition (e.g., CTLA4, LAG3, TIGIT) secondary immune biomarkers were most represented by kidney, gallbladder, and sarcoma (≥40%), with melanoma, esophageal, head & neck, cervical, stomach, and lung cancer least represented (≥15%).ConclusionsOur studies show comprehensive tumor profiling that includes gene expression can detect secondary immune biomarkers targeted by investigational therapies in ~90% of PD-L1-/TMB-/MSS cases. While genomic profiling could also provide therapeutic choices for a percentage of these patients, detection of secondary immune biomarkers by RNA-seq provides additional options for patients without a clear therapeutic path as determined by PD-L1 testing and genomic profiling alone.ReferenceHuang R S P, Haberberger J, Severson E, et al. A pan-cancer analysis of PD-L1 immunohistochemistry and gene amplification, tumor mutation burden and microsatellite instability in 48,782 cases. Mod Pathol 2021;34: 252–263.

Background: Polymorphism within the human T-cell receptor beta variable (TRBV) gene has been proposed as a risk factor for autoimmune disease and immune-related adverse events (IRAEs) during immunotherapy. Previous efforts to evaluate TRBV polymorphism by whole genome sequencing have been hampered by the repetitive nature of the T-cell receptor beta (TCRB) locus. We present a novel long-amplicon TCRB repertoire sequencing approach to enable TRBV haplotype analysis from peripheral blood. Methods: Peripheral blood leukocyte total RNA from 81 Caucasians was used for sequencing of TCRB chains via the Oncomine TCRB-LR assay (amplicon spanning CDR1, 2 and 3) and the Ion Gene Studio S5. VDJ rearrangements were annotated by comparison to the IMGT database, then mined to construct TRBV allele profiles for each individual including, where detected, novel alleles not present in the ImMunoGeneTics (IMGT) database. Finally, TRBV allele profiles were subjected to principal component analysis and k-means clustering to identify TRBV allele haplotypes. Results: Clustering analysis revealed the presence of six major sets of coincident TRBV alleles, which we term haplotype groups. Allelic diversity varied markedly across haplotype groups, with approximately one third of the cohort showing limited TRBV allelic diversity and few uncommon alleles compared to members of other groups. Analysis revealed 37 putatively novel TRBV alleles that are absent from the IMGT database. Conclusion: We demonstrate a straightforward and cost-efficient method for TRBV haplotype analysis from long-amplicon TCRB sequencing data.

We describe the extent to which comprehensive genomic profiling (CGP) results were used by oncologists to guide targeted therapy selection in a cohort of solid tumor patients tested as part of standard care at Roswell Park Comprehensive Cancer Center June 2016–June 2017, with adequate follow up through September 2018 (n = 620). Overall, 28.4% of CGP tests advised physicians about targeted therapy use supported by companion diagnostic or practice guideline evidence. Post-test targeted therapy uptake was highest for patients in active treatment at the time of order (86% versus 76% of treatment naïve patients), but also took longer to initiate (median 50 days versus 7 days for treatment naïve patients), with few patients (2.6%) receiving targeted agents prior to testing. 100% of patients with resistance variants did not receive targeted agents. Treatment naïve patients received immunotherapy as the most common alternative. When targeted therapy given off-label or in a trial was the best CGP option, (7%) of patients received it. Our data illustrate the appropriate and heterogeneous use of CGP by oncologists as a longitudinal treatment decision tool based on patient history and treatment needs, and that some patients may benefit from testing prior to initiation of other standard treatments.

Background We performed profiling of the immune microenvironment of castration-resistant (CRPC) and castration-sensitive (CSPC) prostate cancer (PC) in order to identify novel targets for immunotherapy. Methods PD-L1 and CD3/CD8 immunohistochemistry, PD-L1/2 fluorescent in situ hybridization, tumor mutation burden, microsatellite instability, and RNA-seq of 395 immune-related genes were performed in 19 CRPC and CSPC. Targeted genomic sequencing and fusion analysis were performed in 17 of these specimens. Results CD276, PVR, and NECTIN2 were highly expressed in PC. Comparison of CRPC versus CSPC and primary versus metastatic tissue revealed the differential expression of immunostimulatory, immunosuppressive, and epithelial-to-mesenchymal transition (EMT)-related genes. Unsupervised clustering of differentially expressed genes yielded two final clusters best segregated by CRPC and CSPC status. Conclusion CD276 and the alternative checkpoint inhibition PVR/NECTIN2/CD226/TIGIT pathway emerged as relevant to PC checkpoint inhibition target development.

Background Immunotherapeutic approaches for pancreatic ductal adenocarcinoma (PDAC) are less successful as compared to many other tumor types. In this study, comprehensive immune profiling was performed in order to identify novel, potentially actionable targets for immunotherapy. Methods Formalin-fixed paraffin embedded (FFPE) specimens from 68 patients were evaluated for expression of 395 immune-related markers (RNA-seq), mutational burden by complete exon sequencing of 409 genes, PD-L1 expression by immunohistochemistry (IHC), pattern of tumor infiltrating lymphocytes (TILs) infiltration by CD8 IHC, and PD-L1/L2 copy number by fluorescent in situ hybridization (FISH). Results The seven classes of actionable genes capturing myeloid immunosuppression, metabolic immunosuppression, alternative checkpoint blockade, CTLA-4 immune checkpoint, immune infiltrate, and programmed cell death 1 (PD-1) axis immune checkpoint, discerned 5 unique clinically relevant immunosuppression expression profiles (from most to least common): (I) combined myeloid and metabolic immunosuppression [affecting 25 of 68 patients (36.8%)], (II) multiple immunosuppressive mechanisms (29.4%), (III) PD-L1 positive (20.6%), (IV) highly inflamed PD-L1 negative (10.3%); and (V) immune desert (2.9%). The Wilcoxon rank-sum test was used to compare the PDAC cohort with a comparison cohort (n=1,416 patients) for the mean expressions of the 409 genes evaluated. Multiple genes including TIM3, VISTA, CCL2, CCR2, TGFB1, CD73, and CD39 had significantly higher mean expression versus the comparison cohort, while three genes (LAG3, GITR, CD38) had significantly lower mean expression. Conclusions This study demonstrates that a clinically relevant unique profile of immune markers can be identified in PDAC and be used as a roadmap for personalized immunotherapeutic decision-making strategies.

Timely and accurate identification of molecular alterations in solid tumors is essential for proper management of patients with advanced cancers. This has created a need for rapid, scalable comprehensive genomic profiling (CGP) systems that detect an increasing number of therapeutically-relevant variant types and molecular signatures. In this study, we assessed the analytical performance of the TruSight Oncology 500 High-Throughput assay for detection of somatic alterations from formalin-fixed paraffin-embedded tissue specimens. In parallel, we developed supporting software and automated sample preparation systems designed to process up to 70 clinical samples in a single NovaSeq 6000TM sequencing run with a turnaround time of 99% overall accuracy and precision. Our results demonstrate that the high-throughput CGP assay is a reliable method for accurate detection of molecular alterations in support of precision therapeutics in oncology. The supporting systems and scalable workflow allow for efficient interpretation and prompt reporting of hundreds of patient cancer genomes per week with excellent analytical performance.

Purpose of Study: Cancer testis antigens (CTA) are highly immunogenic genes with the ability to cause cancer-specific immune responses when expressed. Their tumor cell-specific expression makes them a key target of natural T cell response, cancer vaccines, immune checkpoint blockade (ICB), and cell-based immunotherapies in a wide range of tumor types. In this study, we assess the pan-cancer distribution and ICB survival association of CTA burden (CTAB) in real-world solid tumors. Procedure: Three tumor sample cohorts were studied: 1) a pan-cancer discovery cohort to develop a low- and high-CTAB cutoff (n=5450, 39 tumor types), 2) a TCGA cohort (n=19923, 32 tumor types) used to validate the classifier based on CTAB distribution and serve as a non-ICB-treated population, and 3) an ICB-treated retrospective cohort to validate the classification on overall survival (OS) (n=242, 3 tumor types). The expression levels of 17 CTA were measured using targeted RNA-Seq of FFPE tumor samples and then ranked against a pan-cancer reference population. CTAB was calculated for each sample, cohort and tumor type as the sum of the 17 CTA gene expression ranks. The discovery cohort median CTAB of 171 was used to classify all three cohorts into high- and low-CTAB groups. OS analysis was performed on the TCGA and ICB-treated cohorts using a CoxPH regression model to determine the Hazard Ratio (HR). Results: The three cohorts demonstrated overlapping single-peak, left-skewed CTAB distribution curves centered at CTAB values between 170 (discovery cohort) and 256 (retrospective cohort). When grouping by tumor types and ordering by median CTAB, the CTAB distributions for tumor types within all three cohorts were comparable. CoxPH regression analysis revealed an association between the CTAB threshold classifier and OS in both the ICB-treated retrospective and non-ICB TCGA cohorts. However, the direction of this association differed between the two cohorts, with high-CTAB samples having better survival (HR=0.936, p=0.076) in the ICB-treated retrospective cohort and worse survival (HR: 1.007, p=0.084) in the non-ICB-treated cohort. Conclusion: Our studies show that the CTAB distribution was maintained across the discovery and TCGA cohorts and a wide range of tumor types, supporting that the CTAB classifier is valid and histology agnostic. Additionally, when evaluating the ICB and non-ICB-treated cohorts, CTAB demonstrated the ability to predict OS, pointing to the utility of ICB in supporting CTA-specific natural immune response. However, further studies are necessary to verify these mechanisms of response to ICB as well as cancer vaccines and cell-based immunotherapies. Additional validation is needed to establish the predictive utility of CTAB alone and in combination with other immune oncology biomarkers for resistance or response. Citation Format: R.J. Seager, Erik Van Roey, Shuang Gao, Blake Burgher, Paul DePietro, Mary Nesline, Roger Klein, Shengle Zhang, Jeffrey M. Conroy, Sarabjot Pabla. Cancer testis antigen burden: Pan-cancer distribution and survival implications [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 5137.

2561 Background: Lymphocyte Activation Gene 3 (LAG3) or CD223 is an immune checkpoint that can be found on various T cells: CD4+, CD8+, regulatory T cells (Tregs), natural killer T cells, natural killer cells, and plasmacytoid dendritic cells. The expression of LAG3 molecule acts to increase T-cell exhaustion, leading to decreased tumor killing as well as an increase in immune suppressive cytokine release. Many clinical trials of LAG3 inhibitors have had modest effects, but recent data suggests that the LAG3 antibody relatlimab together with nivolumab (anti-PD1) provided greater benefit than nivolumab alone in patients with melanoma. Methods: The RNA expression levels of 397 genes in various types of solid tumors from 514 patients seen at the UCSD Moores Cancer Center were analyzed at a CLIA-licensed laboratory, OmniSeq (https://www.omniseq.com/). Following removal of germline variants, synonymous variants, indels and SNVs with < 5% VAF, TMB is reported as mutations/megabase. Transcript abundance was normalized to internal housekeeping gene profiles and ranked (0-100 percentile) in a standardized manner to a reference population of 735 tumors spanning 35 histologies. Odds ratio for high LAG3 expression was calculated and Bonferroni corrected for multiple genes and cancer histologies with > 40 samples. Results: A total of 116 (22.6%) tumors had high LAG3 (≥75) across 32 different histologies. Cancers with the highest proportion of LAG3 were neuroendocrine (47%), uterine (43%), sarcoma (33%), breast (31%), ovarian (30%), pancreatic (24%), lung (20%), stomach (16%), and colorectal (15%). There was significant association for high LAG3 with high PD-L1 (adj P < 0.001), high PD-1 (adj P < 0.0014), high PD-L2 (adj P < 0.0014), high CTLA-4 (adj P < 0.0014), TMB ≥10 mt/mb (adj P = 0.0504). There was no significant association between histologies colorectal (adj P = 0.1834), breast (adj P = NS), ovarian (adj P = NS), pancreatic (adj P = NS), or gender (adj P = 0.272). Conclusions: High LAG3 was found in almost a quarter of tumor samples and significantly associated with other immune checkpoints with FDA-approved drugs. Ongoing studies combining LAG3 inhibitors and specific immune checkpoint inhibitors may yield more clinical benefit if individualized immunomic transcript interrogation is undertaken, rather than population-based approaches without employment of rationally combined agents matched to each patient’s cancer.

2623 Background: Immune checkpoint inhibitors (ICIs) have emerged as effective treatments in non-small cell lung cancer (NSCLC). While the clinical utility of single agent ICI or in combination with chemotherapy has been well established, there remains an unmet need for the development of biomarkers that can better predict response. To address this need, we developed and applied a combination genomic and immune biomarker strategy to ICI-treated NSCLC patients which identified distinct patient subgroups with differential benefit among single agent or combination ICI treatment strategies. Methods: A discovery cohort (DC) of 5450 tumors across 37 histologies were evaluated by comprehensive genomic and immune profiling of the tumor immune microenvironment. Individual and combination biomarker assessment included PD-L1 IHC, TMB, tumor inflammation (TIGS), cell proliferation (CP) and cancer testis antigen burden (CTAB). From this cohort, combinations of molecular and immune biomarkers were identified and applied to a retrospective cohort (RC) of 225 metastatic NSCLC patients treated with pembrolizumab + chemo or pembrolizumab alone to correlate with response. Comparison of objective response rates (ORR) was performed using Chi-square test. Kaplan-Meir analysis was performed to test for differences in overall survival (OS) and 1-year OS. Results: Unsupervised analysis of the DC revealed four distinct biomarker combination groups that describe underlying tumor immunobiology: tumor dominant (CTAB, TMB, CP High), proliferative (CP High), inflamed (TIGS High), and checkpoint (PDL1, TIGS and TMB High). Application of these biomarker groups to the RC demonstrated significant differences in response to ICI regimens between groups (p = 0.04). Patients in the proliferative group (35.1%, 79/225; median PD-L1 = 20% TPS) treated with single agent pembrolizumab showed a significantly higher ORR (59%; 16/27) compared to pembrolizumab + chemo (27%; 14/52; p = 0.005), significantly improved 1-yr OS (p = 0.03), and trend towards better OS (p = 0.14). Importantly, patients in the inflamed group (16%, 36/225; median PD-L1 = 1% TPS), suggested that pembrolizumab + chemo (ORR 26.1%; 6/23) was not associated with ORR compared to pembrolizumab (ORR 31%; 4/13, p = 0.76), or OS (p = 0.37) and 1-yr OS (p = 0.57). Conclusions: Comprehensive genomic and immune profiling may identify PD-L1 low NSCLC patients who benefit from single agent pembrolizumab. PD-L1 low NSCLC patients with a proliferative phenotype may benefit from single agent pembrolizumab, whereas PD-L1 low cases with an inflamed phenotype may benefit from both single agent and combination pembrolizumab. Although further clinical validation of these predictive biomarker combinations is required, this data-driven approach demonstrates the potential to provide treatment decision support when selecting an ICI therapeutic strategy in lung cancer.

e21167 Background: CGIP analyzes FFPE tumor tissue by DNA/RNA sequencing for SNVs, indels, copy gain/loss, fusions, splice variants, MSI and TMB, along with PD-L1 IHC. A purported advantage of CGIP in NSCLC is the ability to identify targeted and immunotherapy biomarkers to inform clinical management. However, the extent to which CGIP supports treatment decisions and benefits NSCLC patients in various treatment settings is limited. Methods: A retrospective analysis of OmniSeq CGIP results (June 2017-March 2019) and real-world clinical data (through March 2020) for NSCLC patients (n = 300) was performed to evaluate treatment strategies at Roswell Park Comprehensive Cancer Center. Patient targeted and immunotherapies following CGIP were classified as “matched” to biomarker results (established or potentially clinically significant) at the indication level (single or multi-marker results, histology, treatment line) based on AMP/ASCO/CAP guidance for strength of biomarker clinical evidence. We estimated overall survival (OS) from CGIP report date for patients who first received either matched therapy or chemotherapy (and no subsequent matched therapy), and assessed the predictive value of matched therapy for OS in the first or subsequent line setting, adjusting for clinicopathologic covariates. Results: Most CGIP tested patients were female (55%), stage IIIB/IV (89%), ECOG < 2 (83%), non-squamous (86%), treatment naïve (62%), ever smokers (88%). 74% (228) of patients were treated post-CGIP, with 71% receiving at least one matched therapy. Matched therapies received in the frontline setting were supported by the highest (Tier 1A) category of evidence more often than subsequent line therapies (97% vs. 68%). 90% of patients with oncogenic driver mutations received targeted agents (17% of total) and 57% received matched immunotherapy. In the frontline setting, compared to chemotherapy, OS was highest for patients who first received matched targeted therapy (median = 23.4 mo; HR 0.26; p = .004; 95% CI 0.13-0.68) vs matched immunotherapy (median = 17.9 mo; HR 0.38; p = .001; 95% CI 0.21-0.69). Subsequent line, OS was also highest for patients who first received matched targeted therapy (median not est., mean = 27.5 mo; HR 0.20; p = .063; 95% CI 0.04-1.09) vs matched immunotherapy (median = 17.4 mo; HR 0.20; 95% CI 0.04-1.09), however, these differences were non-significant. Conclusions: CGIP supports evidence-based clinical decision making for NSCLC in the first and subsequent line settings and leads to improved survival for patients who receive matched targeted or immunotherapy compared to chemotherapy. Better predictive markers are needed to identify NSCLC patients who are more likely to respond to immunotherapies. Heterogeneity of patient biomarker profiles and treatment strategies over time in real world practice are a challenge to assessing CGIP efficacy.

2555 Background: Although immune checkpoint blockade (ICB) has revolutionized cancer treatment, not all patients with cancer benefit from ICB. One possible explanation for poor responders/resistance is the variable expression level of the target molecules (e.g., PD-1 and PD-L1) in the tumor microenvironment. There are recent or ongoing trials targeting variable pathways for immune evasion (e.g., LAG3 or IDO1). It is therefore of interest to know the expression levels related to variable immune checkpoints so that clinical trials can focus on the patients who can benefit from the cognate treatment. Methods: Overall, 514 patients with various solid tumors seen at the University of San Diego, Moores Center for Personalized Cancer Therapy were analyzed. The expression levels of checkpoint markers (ADORA2A, BTLA, CD276, CTLA4, IDO1, IDO2, LAG3, NOS2, PD-1, PD-L1, PD-L2, PVR, TIGIT, TIM3, VISTA, and VTCN) in the tumor samples were measured through RNA sequencing and normalized to internal housekeeping gene profiles, and ranked from 0 to 100 percentile based on a reference population. The expressions of each checkpoint marker were correlated with cancer types, microsatellite instability (MSI), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) status on immunohistochemistry. Results: In this cohort, 60% were female, median age of 60, and included 30 different tumor types, with colorectal cancer being the most common (27%). The rank values of all checkpoint markers were distributed broadly from 0 to 99 or 100. CD276 and NOS2 had the highest (68th percentile) and lowest (13.5 percentile) median rank values, respectively. When rank values were categorized to “Low” (0-24), “Intermediate” (25-74), and “High” (75-100), 41.6% of patients showed high expression of CD276 while only 13% showed high expression of PD-L1. Each patient had a distinctive protfolio of the categorical expression levels of 16 checkpoint markers. Several checkpoint markers, especially NOS2, showed a significant correlation with cancer type. (median rank values in colorectal, stomach, pancreatic, and breast cancer were 79, 76, 5 and 0 respectively, p < 0.001) Five markers (IDO1, LAG3, PD-1, PD-L1, and TIGIT) showed significant correlation with MSI, while seven markers (CTLA4, IDO1, LAG3, PD-1, PD-L1, PD-L2, and TIGIT) were significantly associated with positive PD-L1 status. However, no significant association was seen based on TMB or tissue-specific grouping of patients. Conclusions: The expression of immune checkpoint markers varies from patient to patient, though transcript expression of several markers correlates with cancer type, MSI, and PD-L1 status. Clinical trials with patient selection based on the expression level of checkpoint markers matched to the corresponding ICB drug are warranted.

Background PD-L1 immunohistochemistry (IHC) testing is suboptimal for predicting patient clinical benefit for checkpoint inhibition, while PD-L1 liquid biopsy is not clinically validated and lacks sensitivity, underscoring the need to include PD-L1 testing in more robust, tissue-efficient, comprehensive, scalable next generation sequencing (NGS) tests. Methods To assess comparability and efficacy of PD-L1 testing by NGS with IHC, we identified NSCLC patients treated by first-line pembrolizumab alone (n=54) or pembrolizumab + chemotherapy (n=49) whose tumors underwent companion diagnostic PD-L1 testing by IHC antibody 22C3 testing (high≥50%; low=1–49%, or negative=0% tissue proportion score), and also by RNA-seq, as part of a comprehensive immune profiling panel. PD-L1 expression by RNA-seq, was measured as a percentile rank, with ≥75 considered ‘high’, and Results More than 75% of IHC high cases were classified as high by RNA-Seq for both treatment groups (p Conclusions PD-L1 status by RNA-seq and IHC appear to be comparable. Unlike PD-L1 IHC however, PD-L1 RNA-seq high status versus not high status is associated with greater survival benefit, indicating PD-L1 by NGS may have utility for pembrolizumab selection.

Background Biomarkers predicting immunotherapy response in metastatic renal cell cancer (mRCC) are lacking. PD-L1 immunohistochemistry is a complementary diagnostic for immune checkpoint inhibitors (ICIs) in mRCC, but has shown minimal clinical utility and is not used in routine clinical practice. Methods Tumor specimens from 56 patients with mRCC who received nivolumab were evaluated for PD-L1, cell proliferation (targeted RNA-seq), and outcome. Results For 56 patients treated with nivolumab as a standard of care, there were 2 complete responses and 8 partial responses for a response rate of 17.9%. Dividing cell proliferation into tertiles, derived from the mean expression of 10 proliferation-associated genes in a reference set of tumors, poorly proliferative tumors (62.5%) were more common than moderately (30.4%) or highly proliferative (8.9%) counterparts. Moderately proliferative tumors were enriched for PD-L1 positive (41.2%), compared to poorly proliferative counterparts (11.4%). Objective response for moderately proliferative (29.4%) tumors was higher than that of poorly (11.4%) proliferative counterparts, but not statistically significant (p = .11). When cell proliferation and negative PD-L1 tumor proportion scores were combined statistically significant results were achieved (p = .048), showing that patients with poorly proliferative and PD-L1 negative tumors have a very low response rate (6.5%) compared to moderately proliferative PD-L1 negative tumors (30%). Conclusions Cell proliferation has value in predicting response to nivolumab in clear cell mRCC patients, especially when combined with PD-L1 expression. Further studies which include the addition of progression-free survival (PFS) along with sufficiently powered subgroups are required to further support these findings.

Synovial sarcoma is the most common pediatric non-rhabdomyosarcoma soft tissue sarcoma and accounts for about 8–10% of all soft tissue sarcoma in childhood and adolescence. The presence of a chromosomal translocation-associated SS18-SSX-fusion gene is causally linked to development of primary synovial sarcoma. Metastases occur in approximately 50–70% of synovial sarcoma cases with yet unknown mechanisms, which led to about 70–80% mortality rate in five years. To explore the possibilities to investigate metastatic mechanisms of synovial sarcoma, we carried out the first genome-wide search for potential genetic biomarkers and drivers associated with metastasis by comparative mutational profiling of 18 synovial sarcoma samples isolated from four patients carrying the primary tumors and another four patients carrying the metastatic tumors through whole exome sequencing. Selected from the candidates yielded from this effort, we examined the effect of the multiple missense mutations of ADAM17, which were identified solely in metastatic synovial sarcoma. The mutant alleles as well as the wild-type control were expressed in the mammalian cells harboring the SS18-SSX1 fusion gene. The ADAM17-P729H mutation was shown to enhance cell migration, a phenotype associated with metastasis. Therefore, like ADAM17-P729H, other mutations we identified solely in metastatic synovial sarcoma may also have the potential to serve as an entry point for unraveling the metastatic mechanisms of synovial sarcoma.

The OncoKids panel is an amplification-based next-generation sequencing assay designed to detect diagnostic, prognostic, and therapeutic markers across the spectrum of pediatric malignancies, including leukemias, sarcomas, brain tumors, and embryonal tumors. This panel uses low input amounts of DNA (20 ng) and RNA (20 ng) and is compatible with formalin-fixed, paraffin-embedded and frozen tissue, bone marrow, and peripheral blood. The DNA content of this panel covers the full coding regions of 44 cancer predisposition loci, tumor suppressor genes, and oncogenes; hotspots for mutations in 82 genes; and amplification events in 24 genes. The RNA content includes 1421 targeted gene fusions. We describe the validation of this panel by using a large cohort of 192 unique clinical samples that included a wide range of tumor types and alterations. Robust performance was observed for analytical sensitivity, reproducibility, and limit of detection studies. The results from this study support the use of OncoKids for routine clinical testing of a wide variety of pediatric malignancies.

We have developed a next-generation sequencing assay to quantify biomarkers of the host immune response in formalin-fixed, paraffin-embedded (FFPE) tumor specimens. This assay aims to provide clinicians with a comprehensive characterization of the immunologic tumor microenvironment as a guide for therapeutic decisions on patients with solid tumors. The assay relies on RNA-sequencing (seq) to semiquantitatively measure the levels of 43 transcripts related to anticancer immune responses and 11 transcripts that reflect the relative abundance of tumor-infiltrating lymphocytes, as well as on DNA-seq to estimate mutational burden. The assay has a clinically relevant 5-day turnaround time and can be conducted on as little as 2.5 ng of RNA and 1.8 ng of genomic DNA extracted from three to five standard FFPE sections. The standardized next-generation sequencing workflow produced sequencing reads adequate for clinical testing of matched RNA and DNA from several samples in a single run. Assay performance for gene-specific sensitivity, linearity, dynamic range, and detection threshold was estimated across a wide range of actual and artificial FFPE samples selected or generated to address preanalytical variability linked to specimen features (eg, tumor-infiltrating lymphocyte abundance, percentage of necrosis), and analytical variability linked to assay features (eg, batch size, run, day, operator). Analytical precision studies demonstrated that the assay is highly reproducible and accurate compared with established orthogonal approaches.