High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC).

BACKGROUND: Despite the impressive outcomes with immune checkpoint inhibitor (ICI) in non-small cell lung cancer (NSCLC), only a minority of the patients show long-term benefits from ICI. In this study, we used retrospective cohorts of ICI treated patients with NSCLC to discover and validate spatially resolved protein markers associated with resistance to programmed cell death protein-1 (PD-1) axis inhibition. METHODS: Pretreatment samples from 56 patients with NSCLC treated with ICI were collected and analyzed in a tissue microarray (TMA) format in including four different tumor regions per patient using the GeoMx platform for spatially informed transcriptomics. 34 patients had assessable tissue with tumor compartment in all 4 TMA spots, 22 with leukocyte compartment and 12 with CD68 compartment. The patients' tissue that was not assessable in fourfold redundancy in each compartment was designated as the validation cohort; cytokeratin (CK) (N=22), leukocytes CD45 (N=31), macrophages, CD68 (N=43). The human whole transcriptome, represented by~18,000 individual genes assessed by oligonucleotide-tagged in situ hybridization, was sequenced on the NovaSeq platform to quantify the RNAs present in each region of interest. RESULTS: 54,000 gene variables were generated per case, from them 25,740 were analyzed after removing targets with expression lower than a prespecified frequency. Cox proportional-hazards model analysis was performed for overall and progression-free survival (OS, PFS, respectively). After identifying genes significantly associated with limited survival benefit (HR>1)/progression per spot per patient, we used the intersection of them across the four TMA spots per patient. This resulted in a list of 12 genes in the tumor-cell compartment (RPL13A, GNL3, FAM83A, CYBA, ACSL4, SLC25A6, EPAS1, RPL5, APOL1, HSPD1, RPS4Y1, ADI1). RPL13A, GNL3 in tumor-cell compartment were also significantly associated with OS and PFS, respectively, in the validation cohort (CK: HR, 2.48; p=0.02 and HR, 5.33; p=0.04). In CD45 compartment, secreted frizzled-related protein 2, was associated with OS in the discovery cohort but not in the validation cohort. Similarly, in the CD68 compartment ARHGAP and PNN interacting serine and arginine rich protein were significantly associated with PFS and OS, respectively, in the majority but not all four spots per patient. CONCLUSION: This work highlights RPL13A and GNL3 as potential indicative biomarkers of resistance to PD-1 axis blockade that might help to improve precision immunotherapy strategies for lung cancer.

Next-generation sequencing (NGS) profiling of matched tumor and circulating tumor DNA (ctDNA) in head and neck squamous cell carcinoma (HNSCC).

OBJECTIVES: The aim of this pilot study was to evaluate the presence of somatic mutations in matched tumor and circulating DNA (ctDNA) samples from patients with primary head and neck squamous cell carcinoma (HNSCC) and assess the association of changes in ctDNA levels with survival. MATERIALS AND METHODS: Our study included 62 patients with stage I-IVB HNSCC treated with surgery or radical chemoradiotherapy with curative intent. Plasma samples were obtained at baseline, at the end of treatment (EOT), and at disease progression. Tumor DNA was extracted from plasma (ctDNA) and tumor tissue (tDNA). The Safe Sequencing System was used assess the presence of pathogenic variants in four genes (TP53, CDKN2A, HRAS and PI3KCA) in both ctDNA and tDNA. RESULTS: Forty-five patients had available tissue and plasma samples. Concordance of genotyping results between tDNA and ctDNA at baseline was 53.3%. TP53 mutations were most commonly identified at baseline in both ctDNA (32.6%) and tDNA (40%). The presence of mutations in this restricted set of 4 genes in tissue samples at baseline was associated with decreased overall survival (OS) [median 58.3 months for patients with mutations vs. 89 months for patients without mutations, p < 0.013]. Similarly, patients presenting with mutations in ctDNA had shorter OS [median 53.8 vs. 78.6 months, p < 0.037]. CtDNA clearance at EOT did not show any association with PFS or OS. CONCLUSIONS: Liquid biopsy enables real-time molecular characterization of HNSCC and might predict survival. Larger studies are needed to validate the utility of ctDNA as a biomarker in HNSCC.

Programmed Death-Ligand 1 and Programmed Death-Ligand 2 mRNAs Measured Using Closed-System Quantitative Real-Time Polymerase Chain Reaction Are Associated With Outcome and High Negative Predictive Value in Immunotherapy-Treated NSCLC.

INTRODUCTION: Immune checkpoint inhibitors (ICIs) have become standard of care in lung cancer management, but only a relatively small percentage of patients treated respond. Current predictive biomarkers, including immunohistochemical detection of programmed death-ligand 1 (PD-L1), are insufficient for determining who will respond or, more importantly in the adjuvant setting, who will not respond to ICI therapy. Here, we investigate an alternative method of assessment of PD-L1 to predict nonresponse. METHODS: This study uses a research use only quantitative real-time reverse transcription polymerase chain reaction assay on the GeneXpert system, to test for the association between four target immune genes, CD274 (PD-L1), PDCD1LG2 (programmed death-ligand 2 [PD-L2]), CD8A, and IRF1, and response to ICI therapy. Tissues were collected from 122 patients with advanced NSCLC before ICI therapy in a retrospective cohort, macrodissected, and analyzed using the GeneXpert. RESULTS: Both high PD-L1 and PD-L2 mRNA expression levels were associated with improved long-term benefit at 24 months (p = 0.047 for both PD-L1 and PD-L2) and overall survival (PD-L1, p = 0.048; PD-L2, p = 0.049). Both PD-L1 and PD-L2 mRNA levels were higher in patients with KRAS mutations. Most importantly, low PD-L1 mRNA level had a high negative predictive value of 0.92 for absence of long-term benefit. CONCLUSIONS: With further validation of this assay in low-stage patients, an assessment of PD-L1 mRNA rather than protein, could be a method to determine which low-stage patients that should not be treated with ICIs in the adjuvant setting. This approach may also be a useful objective method for selecting patients for treatment in the advanced setting.

Spatially resolved proteomic profiling identifies tumor cell CD44 as a biomarker associated with sensitivity to PD-1 axis blockade in advanced non-small-cell lung cancer.

BACKGROUND: Most patients with advanced non-small-cell lung cancer (NSCLC) fail to derive significant benefit from programmed cell death protein-1 (PD-1) axis blockade, and new biomarkers of response are needed. In this study, we aimed to discover and validate spatially resolved protein markers associated with sensitivity to PD-1 axis inhibition in NSCLC. METHODS: We initially assessed a discovery cohort of 56 patients with NSCLC treated with PD-1 axis inhibitors at Yale Cancer Center. Using the GeoMx Digital Spatial Profiling (DSP) system, 71 proteins were measured in spatial context on each spot in a tissue microarray. We used the AQUA method of quantitative immunofluorescence (QIF) to orthogonally validate candidate biomarkers. For external independent validation, we assessed whole tissue sections derived from 128 patients with NSCLC treated with single-agent PD-1 axis inhibitors at the 12 de Octubre Hospital (Madrid) using DSP. We further analyzed two immunotherapy untreated cohorts to address prognostic significance (n=252 from Yale Cancer Center; n=124 from University Clinic of Navarra) using QIF and DSP, respectively. RESULTS: Using continuous log-scaled data, we identified CD44 expression in the tumor compartment (pan-cytokeratin (CK)+) as a novel predictor of prolonged progression-free survival (PFS) (multivariate HR=0.68, p=0.043) in the discovery set. We validated by QIF that tumor CD44 levels assessed as continuous QIF scores were associated with longer PFS (multivariate HR=0.31, p=0.022) and overall survival (multivariate HR=0.29, p=0.038). Using DSP in an independent immunotherapy treated cohort, we validated that CD44 levels in the tumor compartment, but not in the immune compartment (panCK-/CD45+), were associated with clinical benefit (OR=1.22, p=0.018) and extended PFS under PD-1 axis inhibition using the highest tertile cutpoint (multivariate HR=0.62, p=0.03). The effect of tumor cell CD44 in predicting PFS remained significant after correcting for programmed death-ligand 1 (PD-L1) Tumor Proportion Score (TPS) in both cohorts. High tumor cell CD44 was not prognostic in the absence of immunotherapy. Using DSP data, intratumoral regions with elevated tumor cell CD44 expression showed prominent (fold change>1.5, adjusted p<0.05) upregulation of PD-L1, TIM-3, ICOS, and CD40 in two independent cohorts. CONCLUSIONS: This work highlights CD44 as a novel indicative biomarker of sensitivity to PD-1 axis blockade that might help to improve immunotherapy strategies for NSCLC.

Comparison of programmed death-ligand 1 protein expression between primary and metastatic lesions in patients with lung cancer.

Assessment of programmed cell death-ligand 1 (PD-L1) expression by immunohistochemistry (IHC) is the definite diagnostic test to guide treatment for patients with advanced-stage non-small cell lung cancer. Intratumoral heterogeneity and discrepancy of PD-L1 expression between primary and metastatic lesions may increase the risk of tumor misclassification. We performed a retrospective study of the Foundation Medicine, Inc clinical database on lung cancer cases that were evaluated for PD-L1 expression by IHC in the context of routine care. All cases were assessed with the Food and Drug Administration-approved 22C3 pharmDx assay and scoring system. 15,028 lung cancer cases, including 8285 primary tumors and 6743 unmatched metastatic lesions were analyzed. Metastatic lesions (mets) were more frequently high positive (tumor proportion score (TPS) ≥50%) for PD-L1 expression than primary lesions (33.8% vs 28.4%; OR, 1.28; 95% CI, 1.19 to 1.37; p<0.001). Higher levels in mets than primaries were seen in samples from lymph nodes, pleural fluid, soft tissue and adrenal gland but not in those from liver, brain and bone. Metastatic lesions of patients with non-squamous histology were more likely to have TPS ≥50% in comparison with primary (OR, 1.37; 95% CI, 1.27 to 1.49; p<0.001), but this was not the case for patients with squamous histology (OR, 0.89; 95% CI, 0.74 to 1.06; p=0.197). PD-L1 expression varies with respect to histologic subtype, sampling site and gender, but is generally higher in metastatic sites. This observation may affect future patient management and trial design.

Alpha-smooth Muscle Actin Expression in the Stroma Predicts Resistance to Trastuzumab in Patients with Early-stage HER2-positive Breast Cancer.

PURPOSE: The companion diagnostic test for trastuzumab has not changed much in the last 25 years. We used high-plex digital spatial profiling to identify biomarkers besides HER2 that can help predict response to trastuzumab in HER2-positive breast cancer. EXPERIMENTAL DESIGN: Fifty-eight protein targets were measured in three different molecularly defined compartments by the NanoString GeoMx Digital Spatial Profiler (DSP) in a tissue microarray containing 151 patients with breast cancer that received adjuvant trastuzumab as part of the Hellenic Cooperative Oncology Group 10/05 clinical trial. Promising candidate biomarkers were orthogonally validated with quantitative immunofluorescence (QIF). RNA-sequencing data from the Neoadjuvant Lapatinib and/or Trastuzumab Treatment Optimisation Study (NeoALTTO) were accessed to provide independent cohort validation. Disease-free survival (DFS) was the main outcome assessed. Statistical analyses were performed using a two-sided test (α = 0.05) and multiple testing correction (Benjamini-Hochberg method, FDR < 0.1). RESULTS: By DSP, high expression of alpha-smooth muscle actin (α-SMA), both in the leukocyte and stromal compartments, was associated with shorter DFS in univariate analysis (P = 0.002 and P = 0.023, respectively). High α-SMA expression in the stroma was validated by QIF after controlling for estrogen receptor and progesterone receptor status [HR, 3.12; 95% confidence interval (CI), 1.12-8.68; P = 0.029] showing recurrence on trastuzumab in the same cohort. In the NeoALTTO cohort, elevated levels of ACTA2 were predictive for shorter DFS in the multivariate analysis (HR, 3.21; 95% CI, 1.14-9.05; P = 0.027). CONCLUSIONS: This work identifies α-SMA as a novel, easy-to-implement biomarker of resistance to trastuzumab that may be valuable in settings where trastuzumab is combined with other therapies.