Analytical validation of a novel comprehensive genomic profiling informed circulating tumor DNA monitoring assay for solid tumors.

Emerging technologies focused on the detection and quantification of circulating tumor DNA (ctDNA) in blood show extensive potential for managing patient treatment decisions, informing risk of recurrence, and predicting response to therapy. Currently available tissue-informed approaches are often limited by the need for additional sequencing of normal tissue or peripheral mononuclear cells to identify non-tumor-derived alterations while tissue-naïve approaches are often limited in sensitivity. Here we present the analytical validation for a novel ctDNA monitoring assay, FoundationOne®Tracker. The assay utilizes somatic alterations from comprehensive genomic profiling (CGP) of tumor tissue. A novel algorithm identifies monitorable alterations with a high probability of being somatic and computationally filters non-tumor-derived alterations such as germline or clonal hematopoiesis variants without the need for sequencing of additional samples. Monitorable alterations identified from tissue CGP are then quantified in blood using a multiplex polymerase chain reaction assay based on the validated SignateraTM assay. The analytical specificity of the plasma workflow is shown to be 99.6% at the sample level. Analytical sensitivity is shown to be >97.3% at ≥5 mean tumor molecules per mL of plasma (MTM/mL) when tested with the most conservative configuration using only two monitorable alterations. The assay also demonstrates high analytical accuracy when compared to liquid biopsy-based CGP as well as high qualitative (measured 100% PPA) and quantitative precision (<11.2% coefficient of variation).

Pan-Cancer Analysis of Copy-Number Features Identifies Recurrent Signatures and a Homologous Recombination Deficiency Biomarker to Predict Poly (ADP-Ribose) Polymerase Inhibitor Response.

PURPOSE: Copy-number (CN) features reveal the molecular state of cancers and may have predictive and prognostic value in the treatment of cancer. We sought to apply published CN analysis methods to a large pan-cancer data set and characterize ubiquitous CN signatures across tumor types, including potential utility for treatment selection. METHODS: We analyzed the landscape of CN features in 260,333 pan-cancer samples. We examined the association of 10 signatures with genomic alterations and clinical characteristics and trained a machine learning classifier using CN and insertion and deletion features to detect homologous recombination deficiency signature (HRDsig) positivity. Clinical outcomes were assessed using a real-world clinicogenomic database (CGDB) of comprehensive genomic profiling linked to deidentified, electronic health record-derived clinical data. RESULTS: CN signatures were prevalent across cancer types and associated with diverse processes including focal tandem duplications, seismic amplifications, genome-wide loss of heterozygosity (gLOH), and HRD. Our novel HRDsig outperformed gLOH in predicting BRCAness and effectively distinguished biallelic BRCA and homologous recombination-repair wild-type (HRRwt) samples pan-tumor, demonstrating high sensitivity to detect biallelic BRCA in ovarian (93%) and other HRD-associated cancers (80%-87%). Pan-tumor prevalence of HRDsig was 6.4%. HRRwt cases represented a significant fraction of the HRDsig-positive cohort, likely reflecting a population with nongenomic mechanisms of HRD. In ovarian and prostate CGDBs, HRDsig identified more patients than gLOH and had predictive value for poly (ADP-ribose) polymerase inhibitor (PARPi) benefit. CONCLUSION: Tumor CN profiles are informative, revealing diverse processes active in cancer. We describe the landscape of 10 CN signatures in a large pan-cancer cohort, including two associated with HRD. We trained a machine learning-based HRDsig that robustly identified BRCAness and associated with biallelic BRCA pan-tumor, and was predictive of PARPi benefit in real-world ovarian and prostate data sets.

Molecular residual disease detection in resected, muscle-invasive urothelial cancer with a tissue-based comprehensive genomic profiling-informed personalized monitoring assay.

Introduction: Circulating tumor DNA (ctDNA) detection postoperatively may identify patients with urothelial cancer at a high risk of relapse. Pragmatic tools building off clinical tumor next-generation sequencing (NGS) platforms could have the potential to increase assay accessibility. Methods: We evaluated the widely available Foundation Medicine comprehensive genomic profiling (CGP) platform as a source of variants for tracking of ctDNA when analyzing residual samples from IMvigor010 (ClinicalTrials.gov identifier NCT02450331), a randomized adjuvant study comparing atezolizumab with observation after bladder cancer surgery. Current methods often involve germline sampling, which is not always feasible or practical. Rather than performing white blood cell sequencing to filter germline and clonal hematopoiesis (CH) variants, we applied a bioinformatic approach to select tumor (non-germline/CH) variants for molecular residual disease detection. Tissue-informed personalized multiplex polymerase chain reaction-NGS assay was used to detect ctDNA postsurgically (Natera). Results: Across 396 analyzed patients, prevalence of potentially actionable alterations was comparable with the expected prevalence in advanced disease (13% FGFR2/3, 20% PIK3CA, 13% ERBB2, and 37% with elevated tumor mutational burden ≥10 mutations/megabase). In the observation arm, 66 of the 184 (36%) ctDNA-positive patients had shorter disease-free survival [DFS; hazard ratio (HR) = 5.77; 95% confidence interval (CI), 3.84-8.67; P < 0.0001] and overall survival (OS; HR = 5.81; 95% CI, 3.41-9.91; P < 0.0001) compared with ctDNA-negative patients. ctDNA-positive patients had improved DFS and OS with atezolizumab compared with those in observation (DFS HR = 0.56; 95% CI, 0.38-0.83; P = 0.003; OS HR = 0.66; 95% CI, 0.42-1.05). Clinical sensitivity and specificity for detection of postsurgical recurrence were 58% (60/103) and 93% (75/81), respectively. Conclusion: We present a personalized ctDNA monitoring assay utilizing tissue-based FoundationOne® CDx CGP, which is a pragmatic and potentially clinically scalable method that can detect low levels of residual ctDNA in patients with resected, muscle-invasive bladder cancer without germline sampling.

Integrative Analysis of a Large Real-World Cohort of Small Cell Lung Cancer Identifies Distinct Genetic Subtypes and Insights into Histologic Transformation.

Small cell lung cancer (SCLC) is a recalcitrant neuroendocrine carcinoma with dismal survival outcomes. A major barrier in the field has been the relative paucity of human tumors studied. Here we provide an integrated analysis of 3,600 "real-world" SCLC cases. This large cohort allowed us to identify new recurrent alterations and genetic subtypes, including STK11-mutant tumors (1.7%) and TP53/RB1 wild-type tumors (5.5%), as well as rare cases that were human papillomavirus-positive. In our cohort, gene amplifications on 4q12 are associated with increased overall survival, whereas CCNE1 amplification is associated with decreased overall survival. We also identify more frequent alterations in the PTEN pathway in brain metastases. Finally, profiling cases of SCLC containing oncogenic drivers typically associated with NSCLC demonstrates that SCLC transformation may occur across multiple distinct molecular cohorts of NSCLC. These novel and unsuspected genetic features of SCLC may help personalize treatment approaches for this fatal form of cancer. SIGNIFICANCE: Minimal changes in therapy and survival outcomes have occurred in SCLC for the past four decades. The identification of new genetic subtypes and novel recurrent mutations as well as an improved understanding of the mechanisms of transformation to SCLC from NSCLC may guide the development of personalized therapies for subsets of patients with SCLC. This article is highlighted in the In This Issue feature, p. 1501.

Predicting EGFR mutational status from pathology images using a real-world dataset.

Treatment of non-small cell lung cancer is increasingly biomarker driven with multiple genomic alterations, including those in the epidermal growth factor receptor (EGFR) gene, that benefit from targeted therapies. We developed a set of algorithms to assess EGFR status and morphology using a real-world advanced lung adenocarcinoma cohort of 2099 patients with hematoxylin and eosin (H&E) images exhibiting high morphological diversity and low tumor content relative to public datasets. The best performing EGFR algorithm was attention-based and achieved an area under the curve (AUC) of 0.870, a negative predictive value (NPV) of 0.954 and a positive predictive value (PPV) of 0.410 in a validation cohort reflecting the 15% prevalence of EGFR mutations in lung adenocarcinoma. The attention model outperformed a heuristic-based model focused exclusively on tumor regions, and we show that although the attention model also extracts signal primarily from tumor morphology, it extracts additional signal from non-tumor tissue regions. Further analysis of high-attention regions by pathologists showed associations of predicted EGFR negativity with solid growth patterns and higher peritumoral immune presence. This algorithm highlights the potential of deep learning tools to provide instantaneous rule-out screening for biomarker alterations and may help prioritize the use of scarce tissue for biomarker testing.

CD8+ T cell-intrinsic IL-6 signaling promotes resistance to anti-PD-L1 immunotherapy.

Although immune checkpoint inhibitors (ICIs) are established as effective cancer therapies, overcoming therapeutic resistance remains a critical challenge. Here we identify interleukin 6 (IL-6) as a correlate of poor response to atezolizumab (anti-PD-L1) in large clinical trials of advanced kidney, breast, and bladder cancers. In pre-clinical models, combined blockade of PD-L1 and the IL-6 receptor (IL6R) causes synergistic regression of large established tumors and substantially improves anti-tumor CD8+ cytotoxic T lymphocyte (CTL) responses compared with anti-PD-L1 alone. Circulating CTLs from cancer patients with high plasma IL-6 display a repressed functional profile based on single-cell RNA sequencing, and IL-6-STAT3 signaling inhibits classical cytotoxic differentiation of CTLs in vitro. In tumor-bearing mice, CTL-specific IL6R deficiency is sufficient to improve anti-PD-L1 activity. Thus, based on both clinical and experimental evidence, agents targeting IL-6 signaling are plausible partners for combination with ICIs in cancer patients.

Comprehensive pan-cancer genomic landscape of KRAS altered cancers and real-world outcomes in solid tumors.

Recent clinical development of KRAS inhibitors has heightened interest in the genomic landscape of KRAS-altered cancers. We performed a pan-cancer analysis of KRAS-altered samples from 426,706 adult patients with solid or hematologic malignancies using comprehensive genomic profiling; additional analyses included 62,369 liquid biopsy and 7241 pediatric samples. 23% of adult pan-cancer samples had KRAS alterations; 88% were mutations, most commonly G12D/G12V/G12C/G13D/G12R, and prevalence was similar in liquid biopsies. Co-alteration landscapes were largely similar across KRAS mutations but distinct from KRAS wild-type, though differences were observed in some tumor types for tumor mutational burden, PD-L1 expression, microsatellite instability, and other mutational signatures. Prognosis of KRAS-mutant versus other genomic cohorts of lung, pancreatic, and colorectal cancer were assessed using a real-world clinicogenomic database. As specific KRAS inhibitors and combination therapeutic strategies are being developed, genomic profiling to understand co-alterations and other biomarkers that may modulate response to targeted or immunotherapies will be imperative.

Tissue and liquid biopsy profiling reveal convergent tumor evolution and therapy evasion in breast cancer.

Pathological and genomic profiling have transformed breast cancer care by matching patients to targeted treatments. However, tumors evolve and evade therapeutic interventions often through the acquisition of genomic mutations. Here we examine patients profiled with tissue (TBx) and liquid biopsy (LBx) as part of routine clinical care, to characterize the tumor evolutionary landscape and identify potential vulnerabilities in the relapsed setting. Real-world evidence demonstrates that LBx is utilized later in care and identifies associations with intervening therapy. While driver events are frequently shared, acquired LBx alterations are detected in a majority of patients, with the highest frequency in ER+ disease and in patients with longer biopsy intervals. Acquired mutations are often polyclonal and present at lower allelic fractions, suggesting multi-clonal convergent evolution. In addition to well-characterized resistance mutations (e.g., ESR1, NF1, RB1, ERBB2), we observe a diversity of rarer but potentially targetable mutations (e.g., PIK3CA, HRAS/NRAS/KRAS, FGFR1/2/3, BRAF) and fusions (e.g., FGFR1/2, ERBB2, RET), as well as BRCA1/2 reversions through a variety of mechanisms, including splice alterations and structural deletions. This study provides insights on treatment and selection-driven tumor evolution and identifies potential combinatorial treatment options in advanced breast cancer.

Association of CD274 (PD-L1) Copy Number Changes with Immune Checkpoint Inhibitor Clinical Benefit in Non-Squamous Non-Small Cell Lung Cancer.

BACKGROUND: We sought to characterize response to immune checkpoint inhibitor (ICI) in non-squamous non-small cell lung cancer (NSCLC) across various CD274 copy number gain and loss thresholds and identify an optimal cutoff. MATERIALS AND METHODS: A de-identified nationwide (US) real-world clinico-genomic database was leveraged to study 621 non-squamous NSCLC patients treated with ICI. All patients received second-line ICI monotherapy and underwent comprehensive genomic profiling as part of routine clinical care. Overall survival (OS) from start of ICI, for CD274 copy number gain and loss cohorts across varying copy number thresholds, were assessed. RESULTS: Among the 621 patients, patients with a CD274 CN greater than or equal to specimen ploidy +2 (N = 29) had a significantly higher median (m) OS when compared with the rest of the cohort (N = 592; 16.1 [8.9-37.3] vs 8.6 [7.1-10.9] months, hazard ratio (HR) = 0.6 [0.4-1.0], P-value = .05). Patients with a CD274 copy number less than specimen ploidy (N = 299) trended toward a lower mOS when compared to the rest of the cohort (N = 322; 7.5 [5.9-11.3] vs 9.6 [7.9-12.8] months, HR = 0.9 [0.7-1.1], P-value = .3). CONCLUSION: This work shows that CD274 copy number gains at varying thresholds predict different response to ICI blockade in non-squamous NSCLC. Considering these data, prospective clinical trials should further validate these findings, specifically in the context of PD-L1 IHC test results.

Intratumoral CD103+ CD8+ T cells predict response to PD-L1 blockade.

BACKGROUND: CD8+ tissue-resident memory T (TRM) cells, marked by CD103 (ITGAE) expression, are thought to actively suppress cancer progression, leading to the hypothesis that their presence in tumors may predict response to immunotherapy. METHODS: Here, we test this by combining high-dimensional single-cell modalities with bulk tumor transcriptomics from 1868 patients enrolled in lung and bladder cancer clinical trials of atezolizumab (anti-programmed cell death ligand 1 (PD-L1)). RESULTS: ITGAE was identified as the most significantly upregulated gene in inflamed tumors. Tumor CD103+ CD8+ TRM cells exhibited a complex phenotype defined by the expression of checkpoint regulators, cytotoxic proteins, and increased clonal expansion. CONCLUSIONS: Our analyses indeed demonstrate that the presence of CD103+ CD8+ TRM cells, quantified by tracking intratumoral CD103 expression, can predict treatment outcome, suggesting that patients who respond to PD-1/PD-L1 blockade are those who exhibit an ongoing antitumor T-cell response.

C-reactive protein reduction post treatment is associated with improved survival in atezolizumab (anti-PD-L1) treated non-small cell lung cancer patients.

PURPOSE: Overall survival (OS) is the most significant endpoint for evaluation of treatment benefit with checkpoint inhibitors (CPI) in cancer. We evaluated serum C-reactive protein (CRP) in non-small cell lung cancer (NSCLC) trials with atezolizumab (anti-PD-L1) as an early OS surrogate. METHODS: Serum from patients enrolled in randomized Phase II (n = 240) and Phase III (n = 701) trials of NSCLC patients (POPLAR, OAK) who progressed on prior-platinum chemotherapy, were analyzed for CRP levels over time. Patients were grouped by changes in CRP levels post-treatment as either increased (≥ 1.5 fold), decreased (≤ 1.5 fold) or unchanged (within +1.5 fold) relative to pre-treatment levels to assess association with progression free survival (PFS) and OS. RESULTS: Decrease in serum CRP levels at 6 weeks relative to pre-treatment were observed in patients with RECIST1.1 based complete or partial responses (CR/PR) to atezolizumab whereas patients with disease progression (PD) demonstrated an increase in CRP levels in the Phase II POPLAR study, and confirmed in the Phase III OAK study. Decrease in serum CRP as early as six weeks post treatment predicted improved PFS and OS, even in patients who were determined as stable disease (SD) in their first scan. This effect was not observed in the chemotherapy arms. CONCLUSION: Modulation of serum CRP correlates with clinical outcome post-atezolizumab treatment. This routine lab test may provide utility in informing OS signals as early as 6 weeks post-initiation of therapy with CPIs in NSCLC.

A pan-cancer analysis of PD-L1 immunohistochemistry and gene amplification, tumor mutation burden and microsatellite instability in 48,782 cases.

PD-L1 immunohistochemistry (IHC) currently has the most Food and Drug Administration (FDA) approvals as a companion diagnostic (CDx) for immunotherapies in specific tumor types; however, multiple other immunotherapy biomarkers exist. We performed this study to examine and report the prevalence of PD-L1 expression in a wide variety of tumor types and examine its relationship to microsatellite instability (MSI), tumor mutational burden (TMB), and CD274 (PD-L1) gene amplification. We performed a retrospective analysis of all cases in which both PD-L1 IHC (using the DAKO 22C3 IHC assay with either tumor proportion score (TPS) or combined positive score (CPS); or the VENTANA SP142 assay with infiltrating immune cell score (IC)) and comprehensive genomic profiling (CGP) were tested at Foundation Medicine between January 2016 and November 2019. Of note, PD-L1 positivity is defined per the CDx indication and tumor proportion score (TPS ≥ 1) for indications without a CDx claim; and TMB positivity is defined as ≥10 mutations/Mb. A total of 48,782 cases were tested for PD-L1 IHC and CGP. Immune cell expression of PD-L1 was more frequently identified than tumor cell expression of PD-L1. We saw a high correlation between PD-L1 expression and CD274 gene amplification (p < 0.0001), MSI and TMB (p < 0.0001), and PD-L1 and TMB (p < 0.0001). In addition, the combination of PD-L1 and TMB identified four unique disease subsets PD-L1-/TMB-, PD-L1+/TMB-, PD-L1-/TMB+, and PD-L1+/TMB+ with varying prevalence dependent on tumor type. Lastly, 50.3% (24527/48782) of the overall cohort was positive for at least one of the CDx or exploratory biomarkers described above. This is the largest pan-cancer analysis of relevant biomarkers associated with response to checkpoint inhibitors to date, including more than 48,000 cases. Additional clinical trials with treatment outcome data in individual tumor types are needed to determine whether the double positive PD-L1+/TMB+ disease subset would respond best to immunotherapy.

Somatic HLA Class I Loss Is a Widespread Mechanism of Immune Evasion Which Refines the Use of Tumor Mutational Burden as a Biomarker of Checkpoint Inhibitor Response.

Neoantigen presentation arises as a result of tumor-specific mutations and is a critical component of immune surveillance that can be abrogated by somatic LOH of the human leukocyte antigen class I (HLA-I) locus. To understand the role of HLA-I LOH in oncogenesis and treatment, we utilized a pan-cancer genomic dataset of 83,644 patient samples, a small subset of which had treatment outcomes with immune checkpoint inhibitors (ICI). HLA-I LOH was common (17%) and unexpectedly had a nonlinear relationship with tumor mutational burden (TMB). HLA-I LOH was frequent at intermediate TMB, yet prevalence decreased above 30 mutations/megabase, suggesting highly mutated tumors require alternate immune evasion mechanisms. In ICI-treated patients with nonsquamous non-small cell lung cancer, HLA-I LOH was a significant negative predictor of overall survival. Survival prediction improved when combined with TMB, suggesting TMB with HLA-I LOH may better identify patients likely to benefit from ICIs. SIGNIFICANCE: This work shows the pan-cancer landscape of HLA-I LOH, revealing an unexpected "Goldilocks" relationship between HLA-I LOH and TMB, and demonstrates HLA-I LOH as a significant negative predictor of outcomes after ICI treatment. These data informed a combined predictor of outcomes after ICI and have implications for tumor vaccine development.This article is highlighted in the In This Issue feature, p. 211.

Molecular Subsets in Renal Cancer Determine Outcome to Checkpoint and Angiogenesis Blockade.

Integrated multi-omics evaluation of 823 tumors from advanced renal cell carcinoma (RCC) patients identifies molecular subsets associated with differential clinical outcomes to angiogenesis blockade alone or with a checkpoint inhibitor. Unsupervised transcriptomic analysis reveals seven molecular subsets with distinct angiogenesis, immune, cell-cycle, metabolism, and stromal programs. While sunitinib and atezolizumab + bevacizumab are effective in subsets with high angiogenesis, atezolizumab + bevacizumab improves clinical benefit in tumors with high T-effector and/or cell-cycle transcription. Somatic mutations in PBRM1 and KDM5C associate with high angiogenesis and AMPK/fatty acid oxidation gene expression, while CDKN2A/B and TP53 alterations associate with increased cell-cycle and anabolic metabolism. Sarcomatoid tumors exhibit lower prevalence of PBRM1 mutations and angiogenesis markers, frequent CDKN2A/B alterations, and increased PD-L1 expression. These findings can be applied to molecularly stratify patients, explain improved outcomes of sarcomatoid tumors to checkpoint blockade versus antiangiogenics alone, and develop personalized therapies in RCC and other indications.

High systemic and tumor-associated IL-8 correlates with reduced clinical benefit of PD-L1 blockade.

Although elevated plasma interleukin-8 (pIL-8) has been associated with poor outcome to immune checkpoint blockade 1, this has not been comprehensively evaluated in large randomized studies. Here we analyzed circulating pIL-8 and IL8 gene expression in peripheral blood mononuclear cells and tumors of patients treated with atezolizumab (anti-PD-L1 monoclonal antibody) from multiple randomized trials representing 1,445 patients with metastatic urothelial carcinoma (mUC) and metastatic renal cell carcinoma. High levels of IL-8 in plasma, peripheral blood mononuclear cells and tumors were associated with decreased efficacy of atezolizumab in patients with mUC and metastatic renal cell carcinoma, even in tumors that were classically CD8+ T cell inflamed. Low baseline pIL-8 in patients with mUC was associated with increased response to atezolizumab and chemotherapy. Patients with mUC who experienced on-treatment decreases in pIL-8 exhibited improved overall survival when treated with atezolizumab but not with chemotherapy. Single-cell RNA sequencing of the immune compartment showed that IL8 is primarily expressed in circulating and intratumoral myeloid cells and that high IL8 expression is associated with downregulation of the antigen-presentation machinery. Therapies that can reverse the impacts of IL-8-mediated myeloid inflammation will be essential for improving outcomes of patients treated with immune checkpoint inhibitors.

Dendritic cells dictate responses to PD-L1 blockade cancer immunotherapy.

PD-L1/PD-1 blocking antibodies have demonstrated therapeutic efficacy across a range of human cancers. Extending this benefit to a greater number of patients, however, will require a better understanding of how these therapies instigate anticancer immunity. Although the PD-L1/PD-1 axis is typically associated with T cell function, we demonstrate here that dendritic cells (DCs) are an important target of PD-L1 blocking antibody. PD-L1 binds two receptors, PD-1 and B7.1 (CD80). PD-L1 is expressed much more abundantly than B7.1 on peripheral and tumor-associated DCs in patients with cancer. Blocking PD-L1 on DCs relieves B7.1 sequestration in cis by PD-L1, which allows the B7.1/CD28 interaction to enhance T cell priming. In line with this, in patients with renal cell carcinoma or non-small cell lung cancer treated with atezolizumab (PD-L1 blockade), a DC gene signature is strongly associated with improved overall survival. These data suggest that PD-L1 blockade reinvigorates DC function to generate potent anticancer T cell immunity.

Top 10 Challenges in Cancer Immunotherapy.

Cancer immunotherapy is a validated and critically important approach for treating patients with cancer. Given the vast research and clinical investigation efforts dedicated to advancing both endogenous and synthetic immunotherapy approaches, there is a need to focus on crucial questions and define roadblocks to the basic understanding and clinical progress. Here, we define ten key challenges facing cancer immunotherapy, which range from lack of confidence in translating pre-clinical findings to identifying optimal combinations of immune-based therapies for any given patient. Addressing these challenges will require the combined efforts of basic researchers and clinicians, and the focusing of resources to accelerate understanding of the complex interactions between cancer and the immune system and the development of improved treatment options for patients with cancer.