Digital multiplexed analysis of circular RNAs in FFPE and fresh non‐small cell lung cancer specimens

Although many studies highlight the implication of circular RNAs (circRNAs) in carcinogenesis and tumor progression, their potential as cancer biomarkers has not yet been fully explored in the clinic due to the limitations of current quantification methods. Here, we report the use of the nCounter platform as a valid technology for the analysis of circRNA expression patterns in non‐small cell lung cancer (NSCLC) specimens. Under this context, our custom‐made circRNA panel was able to detect circRNA expression both in NSCLC cells and formalin‐fixed paraffin‐embedded (FFPE) tissues. CircFUT8 was overexpressed in NSCLC, contrasting with circEPB41L2, circBNC2, and circSOX13 downregulation even at the early stages of the disease. Machine learning (ML) approaches from different paradigms allowed discrimination of NSCLC from nontumor controls (NTCs) with an 8‐circRNA signature. An additional 4‐circRNA signature was able to classify early‐stage NSCLC samples from NTC, reaching a maximum area under the ROC curve (AUC) of 0.981. Our results not only present two circRNA signatures with diagnosis potential but also introduce nCounter processing following ML as a feasible protocol for the study and development of circRNA signatures for NSCLC.

A PD-1 /PD-L1 proximity assay as a theranostic marker for PD-1 blockade in patients with metastatic melanoma

PURPOSE

Less than 50% of patients with melanoma respond to anti-PD1, and this treatment can induce severe toxicity. Predictive markers are thus needed to improve the benefit/risk ratio of immune checkpoint inhibitors (ICI). Baseline tumor parameters such as PD-L1 expression, CD8⁺ T cell infiltration, mutational burden and various transcriptomic signatures are associated with response to ICI but their predictive values are not sufficient. Interaction between PD1 and its main ligand, PDL1 appears a valuable target of anti-PD1 therapy. Thus, instead of looking at PD-L1 expression only, we evaluated the predictive value of the proximity between PD1 and its neighboring PD-L1 molecules in terms of response to anti-PD1 therapy.

EXPERIMENTAL DESIGN

PD1/PD-L1 proximity was assessed by proximity ligation assay (PLA) on 137 samples from two cohorts (exploratory n=66 and validation n=71) of samples from melanoma patients treated with anti-PD1+/-anti CTLA4. Additional predictive biomarkers such as PD-L1 expression (MELscore), CD8+ cells density and nanostring RNA signature were also evaluated.

RESULTS

A PD1/PD-L1 PLA model was developed to predict tumor response in an exploratory cohort and further evaluated in an independent validation cohort. This score showed higher predictive ability (AUC=0.85 and 0.79, in the two cohorts respectively) for PD1/PD-L1 PLA as compared to other parameters (AUC from 0.71 to 0.77). Progression free and overall survival were significantly longer in patients with high PLA values (p=0.00019 and p<0.0001 respectively).

CONCLUSION

The proximity between PD-1 and PD-L1, easily assessed by this PLA on one FFPE section, appears as a new biomarker of anti-PD1 efficacy.

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.

24 Nivolumab serum concentration in metastatic melanoma patients could be related to anti-tumor activity gene and outcome

Background

Nivolumab (nivo) is a monoclonal antibody that targets programmed death-1 (PD-1) molecule and has been approved for the treatment of several solid tumors; in the treatment of adjuvant and metastatic melanoma had better efficacy compared with chemotherapy or ipilimumab (anti-CTLA4).1–4 The classical dosage of nivo tested in the phase III trials was 3 mg/kg every 2 weeks (Q2W). However, in order to make easier the administration, it was introduced the flat dosage at 240mg every 2 weeks (Q2W) or 480mg every 4 weeks (Q4W).5 6 The purpose of this study was to investigate retrospectively the relationships between the different nivo dosages and their serum concentration; in addition, we also investigated possible relationship with the expression of pro/antitumor activity genes.

Methods

From July 2016 to December 2018 at INT IRCCS Pascale, Naples, we collected serum and RNA samples from 88 patients with metastatic melanoma at week 12 from the first administration of nivo. All patients have appropriately signed informed consent. The ORR among the 88 patients was 25% (patients baseline characteristics are listed in table 1). Commercial ELISA assay were performed in 96 well plates following the protocol procedures. Gene expression profiling was performed using NanoString® IO360 panels on 37 patients (CR: 4, PR: 10, SD: 11, PD: 12). Statistical analysis was performed through the Student’s t-test and via Spearman’s rho correlation coefficient. Gene profiling analysis was performed via Bonferroni correction.

Results

We observed that patients with complete response (CR) have a higher nivo concentration (p=0.003) compared to other groups. No correlation was observed with the most important markers of renal and hepatic function: eGFR, creatinine, AUC, albumin, ALT, AST and gamma GT. Data from gene expression profile shown that patients with CR had a higher expression of anti-tumor and immune activation genes such as: TAPBP, CD47, HDC, IL12RB2 and HLA-DQA1 (P <0.05). Furthermore, genes with pro-tumor or immunosuppressive activity such as MMP9, GOR160, HK2 and LILRA5 (P <0.05) were found to be inversely related with drug concentration while CD1C, a T-cell surface glycoprotein involved in antigen-presenting, it is directly related (p=0.005).

Abstract 24 Table 1

Patients clinical parameters

Conclusions

In this retrospective study we found that higher serum concentration of nivo was correlated with a better outcome and higher frequency of CR. Moreover, in patients with a CR there was an enhancing of the immune activation with an increase of HLA-DQA, TAPBP and IL12RB2. Further investigations are needed to get additional information.

Acknowledgements

The study was supported by the Institutional Project ‘Ricerca Corrente’ of Istituto Nazionale Tumori IRCCS Fondazione ‘G. Pascale’ of Napoli, Italy.

References

James Larkin, Vanna Chiarion-Sileni, Rene Gonzalezet al. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med 2015 Jul 2;373(1):23–34.

Robert C, Long GV, Brady B et al. Nivolumab in previously untreated melanoma without BRAF mutation. N Engl J Med 2015 Jan 22;372(4):320–30.

Weber JS, D’Angelo SP, Minor D et al. Nivolumab versus chemotherapy in patients with advanced melanoma who progressed after anti-CTLA-4 treatment (CheckMate 037): a randomised, controlled, open-label, phase 3 trial. Lancet Oncol 2015 Apr;16(4):375–8.

Weber J, Mandala M, Del Vecchio M, Gogas HJ, Arance AM, Cowey CL, Dalle S,4. Schenker M, Chiarion-Sileni V, Marquez-Rodas I et al. CheckMate 238 Collaborators. Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma. N Engl J Med 2017 Nov 9;377(19):1824–1835.

Zhao X, Suryawanshi S, Hruska M et al. Assessment of nivolumab benefit-risk profile of a 240-mg flat dose relative to a 3-mg/kg dosing regimen in patients with advanced tumors. Ann Oncol 2017 Aug 1;28(8):2002–2008.

Long GV, Tykodi SS, Schneider JG et al. Assessment of nivolumab exposure and clinical safety of 480?mg every 4 weeks flat-dosing schedule in patients with cancer. Ann Oncol 2018 Nov 1;29(11):2208–2213.

Ethics Approval

The study was approved by the internal ethics board of the Istituto Nazionale Tumori IRCCS Fondazione ‘G. Pascale’ of Napoli Italy, approval number of registry 33/17 OSS.

Consent

Written informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.

946 Standardized transcriptional profiling for optimizing cellular therapies: a multi-center PICI-NanoString collaboration

Background

The field of cellular therapy remains one of the most promising areas for the development of new cancer treatments. To further these improvements, it is imperative to broadly understand cell therapy products at the molecular level and to identify factors that contribute to their efficacy. NanoString and the Parker Institute for Cancer Immunotherapy (PICI) have established a ground-breaking collaboration to characterize up to 1,000 apheresis and cellular therapy infusion products with the primary goal to dissect and study molecular pathways that correlate with optimal cellular therapies.

Methods

Using a large and diverse sample cohort collected from eight PICI network Cell Therapy Centers the team will aim to study gene expression profiles (GEP) that correlate with optimal apheresis and downstream cellular products, identifying biomarkers and signatures for clinical response or toxicity and further explore unique cancer-specific and shared characteristics that make an optimal and effective chimeric antigen receptor (CAR) T cell. As shown here, this first of its kind study will include samples that target dozens of different antigens covering both primary and metastatic hematological and solid tumors. Samples will be characterized using the standardized set of genes included in the nCounter CAR-T Characterization Panel and will measure essential components of CAR-T including: metabolic fitness, phenotype, TCR diversity, toxicity, activation, persistence, exhaustion and cell typing along with individual transgene expression.

Results

Presented here are initial questions that will be asked as part of this study. Meta-analysis will be performed as an aggregated set of data and individual site-specific analysis. Data will further be analyzed across individual cancer types, target types, outcome and manufacturing conditions as examples. We anticipate this information will prove useful across many aspects of the development, manufacturing and clinical applications for cellular therapies and further hypothesize that these findings will promote the understanding of pathways affecting safety and efficacy that may help optimize the therapy.

Conclusions

The project is anticipated to begin Fall of 2021 with work continuing in phases through 2022 with periodic data reports to be shared through scientific conferences. All data and findings will be made publicly available to the scientific community through PICI’s Cancer Data and Evidence Library analysis platform (CANDEL).

308 Transcriptomic analysis of melanoma patients in adjuvant setting treated with anti PD1 therapy: real life study

Background

Adjuvant treatment of melanoma patients with immune-checkpoint inhibition (ICI) significantly improved relapse-free survival (RFS).1 In the phase 3 keynote-054 trial showed that pembrolizumab (anti-PD1) administration in adjuvant setting provided a longer RFS (59,8%) than the placebo group (41,4%) at a 3.5-year median follow-up.2 Moreover, 4 years RFS results from the phase 3 checkmate 238 trial, showed a superior efficacy of nivolumab versus ipilimumab in patients with resected AJCC-7 stage III or IV melanoma. RFS rate was of 58% in the nivolumab arm and 45% in the ipilimumab arm.3 Although treatment with ICIs has improved the RFS of melanoma patients in adjuvant setting, there is still a large proportion of patients who do not respond to the treatment and then relapse. The aim of this study was to investigate the molecular mechanisms underlying resistance to anti-PD1 treatment in the adjuvant setting.

Methods

From December 2018 to July 2020, n. 121 melanoma patients in stage III or IV NED were treated with anti-PD1s as adjuvant (minimum follow up of 12 months, range 12–30 months). These patients received nivolumab (n=95) or pembrolizumab (n=26). Distant and local metastases was observed in 33 (27%) and 7 (6%) patients, respectively (patients baseline characteristics are listed in table1). Gene expression profiles, using NanoString IO 360 panel, were performed from peripheral blood mononuclear cell (PBMCs), collected retrospectively, from n.73 patients (of which n.26 had relapse). All patients have appropriately signed informed consent. Statistical analysis was performed via Bonferroni correction, P< 0.05 was considered statistically significant for median stratification.

Results

At a minimum follow-up of 12 months, the 12-month rate of Relapse-free survival was 72%, confirming the data reported by checkmate 238 trial. In the transcriptomic analysis we observed that in patients with local-regional metastases there was a higher expression of ITGA2 (p<0.05), a gene that promotes malignant tumor aggression by up-regulating PD-L1 expression through STAT3 pathway and the downregulation of DUSP1 (p<0.05) that is linked in promotion of angiogenesis, invasion and metastasis. Moreover, in male group we found a higher expression of HLA-DQB1 and HLA-DQA1 which belonged to HLA class II beta chains.

Abstract 308 Table 1

Conclusions

In this preliminary report we found that RFS 1-yr rate is similar to checkmate 238 study, and that patients with local metastasis have a higher expression of genes related to promote PDL1 levels. Further investigations are needed to get additional information.

Acknowledgements

The study was supported by the Institutional Project ”Ricerca Corrente” of Istituto Nazionale Tumori IRCCS Fondazione ”G. Pascale” of Napoli, Italy.

References

Weber J, Mandala M, Del Vecchio M, et al, CheckMate 238 Collaborators. Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma. N Engl J Med 2017 November 9;377(19):1824–1835.

Eggermont AMM, Blank CU, Mandalà M, et al. EORTC melanoma group. Adjuvant pembrolizumab versus placebo in resected stage III melanoma (EORTC 1325-MG/KEYNOTE-054): distant metastasis-free survival results from a double-blind, randomised, controlled, phase 3 trial. Lancet Oncol 2021 May;22(5):643–654.

Ascierto PA, Del Vecchio M, Mandalá M, et al. Adjuvant nivolumab versus ipilimumab in resected stage IIIB-C and stage IV melanoma (CheckMate 238): 4-year results from a multicentre, double-blind, randomised, controlled, phase 3 trial. Lancet Oncol 2020 November;21(11):1465–1477.

Ethics Approval

The study was approved by internal ethics board of the Istituto Nazionale Tumori IRCCS Fondazione ”G. Pascale” of Napoli Italy, approval number of registry 33/17 OSS.

Consent

Written informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.

934 Biological mechanisms in the different etiologies of Merkel cell carcinoma patients: polyomavirus or UV exposure

Background

Merkel cell carcinoma (MCC) is a rare and aggressive skin cancer with neuroendocrine features, and it is associated with elevated mortality. The pathogenesis is associated with presence of clonally integrated Merkel cell polyomavirus (MCPyV) or ultraviolet light (UV) exposure.1 The MCPyV causes up to 80% of MCC tumors in North America and Europe.2–4 Recently immunotherapy is having good results,5 the phase 2 trial JAVELIN Merkel 200 indicated that treatment with Avelumab (PDL1 inhibitor) in patients with metastatic MCC pre-treated have a meaningful long-term survival outcomes respect chemotherapy. Moreover, ORRs were highest in patients with high TMB that were also MCPyV−, PD-L1+ or had a greater CD8+ T cell density at the invasive margin.6 In this study, we investigated the biological signatures in patients with MCPyV or not.

Methods

From April 2011 to June 2018, we collected retrospectively 50 FFPE (Formalin-Fixed Paraffin-Embed) from 37 patients with metastatic MCC and 13 tissues from a secondary metastatic site. All patients have appropriately signed informed consent. We performed an immunohistochemistry assays (IHC) for MCPyV and PDL1. In addition, through the NanoString GeoMx DSP (Digital Spatial Profiling), we analysed 11 patients (6 MCPyV+; 5 MCPyV-) with cutaneous metastasis using a 44-plex antibody cocktail. For each slide we selected three different areas: Intratumoral, extratumoral and tumour border, in each area we selected CD4+ and CD8+ cells in 4 different ROIs (Region of Interest). Statistical analysis was performed via Bonferroni correction, P< 0.05 was considered statistically significant for median stratification.

Results

The DSP analysis showed that the tumour border cells have an overexpression of IDO respect intratumoral area (adj. p<0.01). Instead, extratumoral area of MCPyV- patients have a higher expression of B7-H3 respect MCPyV+ as well as FOXP3 is higher in the tumour border of MCPyV+ patients and EpCAM in the intratumoral area (p<0.05). PDL1 is overexpressed in MCPyV+ CD4+ cells respect CD8+ (p<0.05). The IHC assay shown that viral status does not change in multiple metastases and PDL1 is elevated in the tumour border (p<0.05).

Conclusions

In this retrospective study, our preliminary data shown that tumour edge have an important role in the modulations of immune infiltrate and patients with Merkel cell polyomavirus could have a different pathway of immunosuppression compared to patients with non-virus related etiology. Further investigations are needed to get additional information.

Acknowledgements

The study was supported by the Institutional Project ”Ricerca Corrente” of Istituto Nazionale Tumori IRCCS Fondazione ”G. Pascale” of Napoli, Italy.

References

Kaae J, Hansen AV, Biggar RJ, et al. Merkel cell carcinoma: incidence, mortality, and risk of other cancers. J Natl Cancer Inst 2010 June 2;102(11):793–801.

Feng H, Shuda M, Chang Y, et al. Clonal integration of a polyomavirus in human Merkel cell carcinoma. Science 2008 February 22;319(5866):1096–100.

Garneski KM, Warcola AH, Feng Q, et al. Merkel cell polyomavirus is more frequently present in North American than Australian Merkel cell carcinoma tumors. J Invest Dermatol 2009 January;129(1):246–8.

Goh G, Walradt T, Markarov V, et al. Mutational landscape of MCPyV-positive and MCPyV-negative Merkel cell carcinomas with implications for immunotherapy. Oncotarget 2016 January 19;7(3):3403–15.

Bichakjian CK, Olencki T, Aasi SZ, et al. Merkel cell carcinoma, version 1.2018, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw 2018 June;16(6):742–774.

D’Angelo SP, Bhatia S, Brohl AS, et al. Avelumab in patients with previously treated metastatic Merkel cell carcinoma: long-term data and biomarker analyses from the single-arm phase 2 JAVELIN Merkel 200 trial. J Immunother Cancer 2020 May;8(1):e000674.

Ethics Approval

The study was approved by internal ethics board of the Istituto Nazionale Tumori IRCCS Fondazione ”G. Pascale” of Napoli Italy, approval number of registry 33/17 OSS.

Consent

Written informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.

Abstract 466: Differential expression of circRNAs allows discrimination of NSCLC from cancer-free lung specimens using the nCounter platform

Introduction: Lung cancer mortality ranks as the highest of the cancer-related deaths. Studies on tumor profiling at the genomic, transcriptomic and proteomic level has soared in the last decade improving overall survival of these patients by shaping the current targeted therapies; however, further investigation of novel biomarkers for an early diagnosis still remains imperative.circRNAs are a class of tissue-specific stable structures that control mammalian transcription. Their aberrant expression plays an important role in carcinogenesis and tumor progression which profiles them as valuable biomarkers; Conversely, its potential has not been fully explored in lung cancer due to several limitations of current circRNA quantification methods that prevent their clinical implementation.The nCounter technology allows for quantitative and qualitative assessment of up to 800 targets providing an accurate and factual perspective of expression levels. To our knowledge, thru this study we stand as the first on assessing circRNA differential expression with this platform for lung cancer detection both in FFPE specimens and cell lines providing preliminary evidence of their differential expression in lung cancer.

Methods: Cells were cultured under standard conditions until harvested. RNA was isolated by using Allprep DNA/RNA/miRNA universal kit (Qiagen). FFPE lung tissue samples (n=28; 18 NSCLC,10 non-cancer) were retrospectively collected and micro-dissected. RNA was isolated with High Pure FFPET RNA isolation kit (Roche) and quantified by Qubit (Thermo Fisher).Overnight hybridization and posterior nCounter FLEX processing were performed following NanoString protocol for nCounter Elements. Expression analysis was carried out based on a tailored panel of 85 circRNAs related to the biology of the disease.

Results: FFPE lung tissues revealed a cluster of differentially expressed circRNAs that allow distinction of lung cancer versus control. circFOXP1, circEPB41L2 and circBNC2 ranked as the most downregulated circRNAs, whereas circCHD9, circAASDH, circRUNX1 and circCHST15 led the catalog of most upregulated in cancer specimens. circRNA expression of A549, H2228, H3122, PC9, H1666, and HOP-62 cells was compared to the CCL-171 fibroblast cell line. circEPB41L2 and circFOXP1 were also confirmed distinctly downregulated in cancer cell lines.

Conclusion: This study presents for the first time the use of the differential expression of circRNAs in FFPE tissues for lung cancer discrimination using the nCounter platform. While more samples are currently being collected to increase the statistical power of the study, these results pave the way for the developing of future circRNA-based nCounter tests for lung cancer diagnosis. Further experiments using epithelial cells as control will be carried out and results will be pertinently updated at the time of the meeting.

Citation Format: Carlos Pedraz-Valdunciel, Miguel Ángel Molina-Vila, Stavros Giannoukakos, Nicolas Potie, Ruth Roman-Llado, Jill Bracht, Martyna Filipska, Masaoki Ito, Ana Gimenez-Capitán, Cristina Aguado-Esteban, Sarah Warren, Chung-Ying Huang, Trever Bivona, Rafael Rosell. Differential expression of circRNAs allows discrimination of NSCLC from cancer-free lung specimens using the nCounter platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 466.

Abstract 339: Resistance to trastuzumab is associated with alpha-smooth muscle actin expression in the stroma of patients with HER2+ breast cancer

Background: Approximately 15-20% of women diagnosed with breast cancer have HER2+ disease. Trastuzumab is currently FDA approved for the treatment of HER+ breast cancer, based on assessment of HER2 status by the combination of IHC and FISH assays. We hypothesized that there are biomarkers besides HER2 that can help predict response, or resistance, to trastuzumab in HER2+ breast cancer.

Methods: We used the NanoString® GeoMx® Digital Spatial Profiler (DSP) to measure 58 protein targets in three different enriched compartments (tumor [PanCK+], leukocyte [CD45+/CD68-] and macrophage [CD68+]) in a cohort of 151 breast cancer patients that received trastuzumab in the adjuvant setting, represented in a tissue microarray. To assess stromal protein expression, leukocyte and macrophage compartments were analyzed in aggregate. Spatially-resolved proteins were correlated with disease-free survival (DFS). Then, we used multiplexed quantitative immunofluorescence (QIF), performed on the AQUA platform, to validate our findings. Statistical analyses were performed using a two-sided test (α=0.05) and multiple testing correction (Benjamini-Hochberg method, FDR&lt;0.10).

Results: We assessed 58 individual protein targets in four compartments resulting in 282 candidate biomarkers per patient. After adjusting for multiple testing, high expression of alpha-smooth muscle actin (a-SMA) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), both measured in the leukocyte compartment, were associated with shorter DFS in univariate analysis (p=0.045 and p=0.084, respectively); high expression of a-SMA in the stroma was also associated with worse outcome (HR, 4.94; 95% CI, 1.07-22.86; unadjusted p=0.023). Digital counts of a-SMA were inversely correlated with immune cell infiltration in the stroma. Using QIF, and after adjusting for four clinical prognostic factors (stage, grade, ER status and PR status), we validated that high a-SMA expression in the stroma was predictive for shorter DFS (HR, 3.34; 95% CI, 1.18-9.48, p=0.023) in the same cohort.

Conclusions: This work supports the role of cancer-associated fibroblasts in the tumor microenvironment in orchestrating the immune response and mediating resistance to trastuzumab for patients with HER2+ breast cancer. In light of the many new HER2 targeted therapies, this observation identifies a-SMA as a potential biomarker to augment the predictive value of the current standard of care HER2 assay and justifies further validation.

Citation Format: Ioannis A. Vathiotis, Myrto K. Moutafi, Prajan Divakar, Thazin Nwe Aung, Aileen Fernandez, Vesal Yaghoobi, Saba Shafi, Konstantinos N. Syrigos, George Fountzilas, Lajos Pusztai, Sarah Warren, David L. Rimm. Resistance to trastuzumab is associated with alpha-smooth muscle actin expression in the stroma of patients with HER2+ breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 339.

Abstract 1623: Response and skin toxicity related protein signature in late stage melanoma patients after anti-PD-1 treatment

Skin toxicity after anti-PD1 treatment in melanoma patients is the most common type of immune related adverse effect (irAE) and has been associated with improved overall response rate and survival. Nonetheless, not many mechanistic biomarkers have been identified so far, that could be associated with low-grade skin toxicity and good response rates. In this study we have addressed this question by analyzing tumor tissue samples from late-stage melanoma patients with first-line anti-PD1 treatment. Samples obtained prior to treatment were submitted for an unbiased deep proteomic analysis using mass spectrometry (LC-MS) and a targeted transcriptomic analysis. Using the unbiased analysis as a discovery platform we were able to define a potential biomarker panel associated not only with improved response but also low-grade skin toxicity. Unbiased quantification of proteins in tumor tissues was done using data-independent acquisition (DIA) LC-MS technology. Proteins from tissue samples were denatured, digested, and analyzed on a mass spectrometer. A deep spectral library was generated, and proteins were quantified using Spectronaut software (Biognosys). In addition, from the same tumor tissue RNA was extracted and subjected to transcriptomic analysis with NanoString nCounter using the PanCancer IO 360 panel. Subsequent data analysis was done using a sPLS-DA using combined factor of skin toxicity and response. Unbiased analysis of 22 baseline tumor tissue samples from late-stage melanoma patients treated in first line with anti-PD1 resulted in identification and quantification of more than 8000 proteins. Progression free survival analysis showed difference between patients with reported low-grade skin toxicity against all others. Therefore, for sPLS-DA both factors, presence/absence of skin toxicity and response status, were used (non-responders with low-grade skin toxicity were not present in this cohort). Complete separation of subjects was achieved with a panel of 21 proteins. This panel was used for hierarchical clustering and was able to fully restore all three groups of patients. Among all proteins identified in the proteomic panel, melanoma-associated antigen C1 (MAGEC1) has been also assessed in the targeted transcriptomic analysis and represents strikingly similar results. MAGEC1 is also found as a strong predictor in the Human Protein Atlas project. Interestingly, MAGE protein family are tumor-specific antigens that can be recognized by autologous cytolytic T lymphocytes and could serve as a novel ICI target or predictive biomarker. In this study we confirm prior observations of a survival benefit related to irAEs after treatment with PD-1 blockade in late-stage melanoma patients. We also demonstrate the power of deep proteomic profiling and transcriptomic analysis in molecular biomarker selection associated to response and irAEs which further benefit patient survival.

Citation Format: Jakob Vowinckel, Domenico Mallardo, Kamil Sklodowski, Martin Soste, Mariaelena Capone, Gabriele Madonna, Vito Vanella, Sarah Warren, Kristina Beeler, Paolo A. Ascierto. Response and skin toxicity related protein signature in late stage melanoma patients after anti-PD-1 treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1623.

Abstract 2606: A nCounter-Based mRNA signature in plasma associates with localized non-small cell lung cancer

Background: 80% of non-small cell lung cancer (NSCLC) cases are diagnosed at stages IIIB-IV and have a dismal prognosis with a median life expectancy that does not exceed 2 years. In contrast, patients diagnosed at early and locally advanced stages (I-IIIA) can undergo surgery and have the potential to be totally cured. Imaging technologies often detect lung nodules of unknown significance that pose a diagnostic challenge; some patients with benign nodules are submitted to unnecessary surgical interventions while others with small tumors are just kept in observation, risking a significant delay for treatment. A diagnostic test that could differentiate between benign and malignant masses would be of great help in this setting.

Methods: Circulating-free RNA (cfRNA) was isolated from the plasma of healthy individuals (N=21), early(I-II) stage (N=22) and stage IIIA (N=12) NSCLC patients, using an automatic extraction method(Qiasymphony, Qiagen). Purified cfRNA was quantified using Qubit, retrotranscribed and pre-amplified (14cycles) using the Low RNA Input Amplification kit (NanoString Technologies). Gene expression analysis was performed on the nCounter platform using the PanCancer IO360TM (NanoString Technologies), which can detect 770 transcripts related to tumor biology, micro-environment and the immune system.

Results: Gene expression analysis revealed differential patterns for some cf-mRNAs from localized stage NSCLC patients versus healthy controls. A bioinformatics recursive feature elimination algorithm selected a 16-gene mRNA signature that was able to distinguish between localized NSCLC and control samples with an area under the ROC curve of 0.91 to 0.95. Furthermore, the signature scores derived from the algorithm were significantly different between the two cohorts.

Conclusions: We have found an 16-gene signature that can differentiate between cfRNA of localized stages NSCLC patients and control individuals. Our results warrant validation studies in larger cohorts.

Citation Format: Ana Giménez Capitán, Jillian Bracht, Nicolas Potie, María González-Cao, Santiago Viteri, Alejandro Martínez-Bueno, Carlos Cabrera-Gálvez, Pablo Rubinstein, Clara Mayo-de-las-Casas, Joselyn Valarezo, Chung-Ying Huang, Carlos Pedraz, Richard Boykind, Sarah Warren, Rafael Rosell, Miguel Ángel Molina-Vilaa, Andrés Aguilar-Hernández. A nCounter-Based mRNA signature in plasma associates with localized non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2606.

COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets

COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure^1-4, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63⁺ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments.

Abstract 409: A pre-treatment plasma extracellular vesicle-mRNA signature associates with checkpoint inhibitor pneumonitis in lung cancer patients

Introduction: Immune checkpoint inhibitors (ICIs) have demonstrated clinical efficacy in non-small cell lung cancer (NSCLC) patients (p). However, ICIs can also trigger a self-reactive response in the adjacent healthy lung tissue that can eventually lead to life-threatening immune-related adverse events (irAEs), like checkpoint inhibitor pneumonitis (CIP). We hypothesized that a pre-treatment state of chronic inflammation or immune system imbalance could predict which p are at higher risk of developing CIP.

Methodology: We retrospectively collected pre-ICI-treatment FFPE tumor tissue and matching plasma samples from 17 CIP- and 24 non-CIP lung cancer p. An additional 40 plasma samples, including 3 CIP and 37 non-CIP p were used as a validation cohort. The miRCURY exosome isolation kit (Qiagen) was used for extracellular vesicle (EV) enrichment from 500 μL of plasma and RNA was extracted using TRI-reagent. EV-mRNA was then pre-amplified (10 cycles) using the Low RNA Input Amplification kit (NanoString Technologies). FFPE mRNA was extracted using the High Pure FFPET RNA Isolation Kit (Roche). Gene expression analysis was performed on tissue and EV-derived mRNA using the NanoString nCounter platform with the Human PanCancer IO360 panel, which targets 770 genes related to tumor biology, immune response and microenvironment. Differential expression (DE) analysis was carried out based on the development of CIP. Finally, a classifier was created using a bioinformatic recursive feature elimination and a leave-one-out cross validation algorithm to predict which combination of genes is most effective to predict CIP development.

Results: DE analysis revealed 54 differentially expressed genes (DEGs) in pre-treatment tissue of CIP vs. non-CIP p. An 8-gene CIP mRNA signature was able to distinguish between the two cohorts with areas under the ROC curve (AUC) of 0.81-0.95. When analyzing plasma EV samples, we found 57 DEGs. The tissue CIP signature was not translatable to EVs, yielding AUCs of only 0.53-0.54. Therefore, we developed a new 4-gene EV-based mRNA signature that could differentiate CIP vs. non-CIP developing p with AUCs of 0.82-0.90 and an overall accuracy of 89.9%. The negative- and positive predictive values (NPV and PPV) were 92.7% and 78.6%, respectively with a Youden´s index of 0.67. The 4 genes included in the EV signature were upregulated in CIP p and were found to be involved in T-cell activation and immune cell localization to the tumor.

Conclusions: We have created a 4-gene EV-mRNA signature that associates with CIP development upon ICI treatment. Our results also indicate that plasma EV-mRNA was non-inferior to invasive tissue biopsy analysis in predicting CIP development. Validation studies in larger patient cohorts are ongoing.

Citation Format: Jillian Wilhelmina Bracht, Santiago Viteri-Ramirez, Andrés Aguilar, Silvia Calabuig-Fariñas, Juan José García-Mosquera, Chung-Ying Huang, Elena Duréndez-Sáez, Nicolas Potie, Erika Aldeguer, Ana Gimenez-Capitán, Sonia Rodriguez, Ruth Roman, Cristina Aguado, Sarah Warren, Carlos Camps, Rafael Rosell, Eloisa Jantus-Lewintre, Miguel-Angel Molina-Vila, Maria González-Cao. A pre-treatment plasma extracellular vesicle-mRNA signature associates with checkpoint inhibitor pneumonitis in lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 409.

Proteomics meets transcriptomics: Identification of tumor tissue signatures specific to anti-PD1 treatment in late-stage melanoma patients

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Background: Despite advances of anti-PD1 treatment in melanoma, still large subset of patients does not respond or relapses due to primary or acquired resistance. One potential way to overcome the mechanisms of resistance is to identify molecular signatures associated with response to treatment. Here, we are presenting the results of an integrated deep transcriptomic and proteomic analysis of melanoma tissue samples coming from patients prior the treatment with anti-PD1. The combination of targeted transcriptomic approach with unbiased proteomic approach allowed for identification of a molecular response signature specific to anti-PD1 therapy. Methods: Unbiased quantification of proteins in tumor tissues was done using data-independent acquisition (DIA) LC-MS technology. Proteins from tissue samples were denatured, digested, and analyzed on a mass spectrometer. A deep spectral library was generated, and proteins were quantified using Spectronaut software (Biognosys). From the same tumor tissue RNA was extracted and subjected to transcriptomic analysis with NanoString nCounter using the PanCancer IO 360 panel. Integration analysis using latent components, a generalized PLS and sparse sGCCA method implemented in R mixOmics package was used for signature discovery. Results: Studied cohort was balanced for gender, BRAF mutations and stage. Treatment included Nivolumab or Pembrolizumab. Only among responding subjects, low grade (≤ 2) skin toxicity was identified at a significant level (p-value < 0.05). In total, 22 samples were measured (nine non-responders and 13 responders). Overall, the analysis of proteome across all samples resulted in 8548 proteins being identified and quantified. The IO 360 panel contained 770 targets. In combined analysis, 10 mRNA targets together with 64 protein targets were highly associated with response to treatment. Two top candidates identified for mRNA and proteins were SIGLEC5 and ACP6 respectively. The panel of 74 features was sufficient to separate all subjects using unsupervised hierarchical clustering into to two main clusters enriched for responders and non-responders (p-value < 0.05). String-DB analysis revealed numerous interactions and associations within identified panel. Functional analysis using GO enrichment showed major involvement of the selected mRNA and proteins in T-cell regulation as well as in neutrophil degranulation and antigen receptor mediated signaling. Conclusions: Combination of both omics assays provides a very comprehensive image of tumor tissue responses to anti-PD1 treatment in late-stage melanoma patients. Identified candidates show striking changes in responder and non-responder groups and should undergo further validation for use in precision medicine.

The spatial landscape of lung pathology during COVID-19 progression

Recent studies have provided insights into the pathology of and immune response to COVID-191-8. However, a thorough investigation of the interplay between infected cells and the immune system at sites of infection has been lacking. Here we use high-parameter imaging mass cytometry9 that targets the expression of 36 proteins to investigate the cellular composition and spatial architecture of acute lung injury in humans (including injuries derived from SARS-CoV-2 infection) at single-cell resolution. These spatially resolved single-cell data unravel the disordered structure of the infected and injured lung, alongside the distribution of extensive immune infiltration. Neutrophil and macrophage infiltration are hallmarks of bacterial pneumonia and COVID-19, respectively. We provide evidence that SARS-CoV-2 infects predominantly alveolar epithelial cells and induces a localized hyperinflammatory cell state that is associated with lung damage. We leverage the temporal range of fatal outcomes of COVID-19 in relation to the onset of symptoms, which reveals increased macrophage extravasation and increased numbers of mesenchymal cells and fibroblasts concomitant with increased proximity between these cell types as the disease progresses-possibly as a result of attempts to repair the damaged lung tissue. Our data enable us to develop a biologically interpretable landscape of lung pathology from a structural, immunological and clinical standpoint. We use this landscape to characterize the pathophysiology of the human lung from its macroscopic presentation to the single-cell level, which provides an important basis for understanding COVID-19 and lung pathology in general.

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

Multiplex Detection of Clinically Relevant Mutations in Liquid Biopsies of Cancer Patients Using a Hybridization-Based Platform

BACKGROUND

With the advent of precision oncology, liquid biopsies are quickly gaining acceptance in the clinical setting. However, in some cases, the amount of DNA isolated is insufficient for Next-Generation Sequencing (NGS) analysis. The nCounter platform could be an alternative, but it has never been explored for detection of clinically relevant alterations in fluids.

METHODS

Circulating-free DNA (cfDNA) was purified from blood, cerebrospinal fluid, and ascites of patients with cancer and analyzed with the nCounter 3 D Single Nucleotide Variant (SNV) Solid Tumor Panel, which allows for detection of 97 driver mutations in 24 genes.

RESULTS

Validation experiments revealed that the nCounter SNV panel could detect mutations at allelic fractions of 0.02-2% in samples with ≥5 pg mutant DNA/µL. In a retrospective analysis of 70 cfDNAs from patients with cancer, the panel successfully detected EGFR, KRAS, BRAF, PIK3CA, and NRAS mutations when compared with previous genotyping in the same liquid biopsies and paired tumor tissues [Cohen kappa of 0.96 (CI = 0.92-1.00) and 0.90 (CI = 0.74-1.00), respectively]. In a prospective study including 91 liquid biopsies from patients with different malignancies, 90 yielded valid results with the SNV panel and mutations in EGFR, KRAS, BRAF, PIK3CA, TP53, NFE2L2, CTNNB1, ALK, FBXW7, and PTEN were found. Finally, serial liquid biopsies from a patient with NSCLC revealed that the semiquantitative results of the mutation analysis by the SNV panel correlated with the evolution of the disease.

CONCLUSIONS

The nCounter platform requires less DNA than NGS and can be employed for routine mutation testing in liquid biopsies of patients with cancer.

A single-cell and spatial atlas of autopsy tissues reveals pathology and cellular targets of SARS-CoV-2

The SARS-CoV-2 pandemic has caused over 1 million deaths globally, mostly due to acute lung injury and acute respiratory distress syndrome, or direct complications resulting in multiple-organ failures. Little is known about the host tissue immune and cellular responses associated with COVID-19 infection, symptoms, and lethality. To address this, we collected tissues from 11 organs during the clinical autopsy of 17 individuals who succumbed to COVID-19, resulting in a tissue bank of approximately 420 specimens. We generated comprehensive cellular maps capturing COVID-19 biology related to patients' demise through single-cell and single-nucleus RNA-Seq of lung, kidney, liver and heart tissues, and further contextualized our findings through spatial RNA profiling of distinct lung regions. We developed a computational framework that incorporates removal of ambient RNA and automated cell type annotation to facilitate comparison with other healthy and diseased tissue atlases. In the lung, we uncovered significantly altered transcriptional programs within the epithelial, immune, and stromal compartments and cell intrinsic changes in multiple cell types relative to lung tissue from healthy controls. We observed evidence of: alveolar type 2 (AT2) differentiation replacing depleted alveolar type 1 (AT1) lung epithelial cells, as previously seen in fibrosis; a concomitant increase in myofibroblasts reflective of defective tissue repair; and, putative TP63+ intrapulmonary basal-like progenitor (IPBLP) cells, similar to cells identified in H1N1 influenza, that may serve as an emergency cellular reserve for severely damaged alveoli. Together, these findings suggest the activation and failure of multiple avenues for regeneration of the epithelium in these terminal lungs. SARS-CoV-2 RNA reads were enriched in lung mononuclear phagocytic cells and endothelial cells, and these cells expressed distinct host response transcriptional programs. We corroborated the compositional and transcriptional changes in lung tissue through spatial analysis of RNA profiles in situ and distinguished unique tissue host responses between regions with and without viral RNA, and in COVID-19 donor tissues relative to healthy lung. Finally, we analyzed genetic regions implicated in COVID-19 GWAS with transcriptomic data to implicate specific cell types and genes associated with disease severity. Overall, our COVID-19 cell atlas is a foundational dataset to better understand the biological impact of SARS-CoV-2 infection across the human body and empowers the identification of new therapeutic interventions and prevention strategies.

The effect of confounding data features on a deep learning algorithm to predict complete coronary occlusion in a retrospective observational setting

Aims

Deep learning (DL) has emerged in recent years as an effective technique in automated ECG analysis.

Methods and results

A retrospective, observational study was designed to assess the feasibility of detecting induced coronary artery occlusion in human subjects earlier than experienced cardiologists using a DL algorithm. A deep convolutional neural network was trained using data from the STAFF III database. The task was to classify ECG samples as showing acute coronary artery occlusion, or no occlusion. Occluded samples were recorded after 60 s of balloon occlusion of a single coronary artery. For the first iteration of the experiment, non-occluded samples were taken from ECGs recorded in a restroom prior to entering theatres. For the second iteration of the experiment, non-occluded samples were taken in the theatre prior to balloon inflation. Results were obtained using a cross-validation approach. In the first iteration of the experiment, the DL model achieved an F1 score of 0.814, which was higher than any of three reviewing cardiologists or STEMI criteria. In the second iteration of the experiment, the DL model achieved an F1 score of 0.533, which is akin to the performance of a random chance classifier.

Conclusion

The dataset was too small for the second model to achieve meaningful performance, despite the use of transfer learning. However, 'data leakage' during the first iteration of the experiment led to falsely high results. This study highlights the risk of DL models leveraging data leaks to produce spurious results.

High-Throughput Simultaneous mRNA Profiling Using nCounter Technology Demonstrates That Extracellular Vesicles Contain Different mRNA Transcripts Than Their Parental Prostate Cancer Cells

Extracellular vesicles (EVs) are nano-sized lipid bilayer encapsulated particles with a molecular cargo that appears to play important roles within the human body, such as in cell-to-cell communication. Unraveling the composition of EV cargos remains one of the most fundamental steps toward understanding the role of EVs in intercellular communication and the discovery of new biomarkers. One of the unmet needs in this field is the lack of a robust, sensitive, and multiplexed method for EV mRNA profiling. We established a new protocol using the NanoString low RNA input nCounter assay by which the targeted mRNA transcripts in EVs can be efficiently and specifically amplified and then assayed for 770 mRNAs in one reaction. Prostate cancer cells with epithelial (PC3-Epi) or mesenchymal (PC3-EMT) phenotypes and their progeny EVs were analyzed by the same panel. Among these mRNAs, 157 were detected in PC3-Epi EVs and 564 were detected in PC3-EMT EVs. NOTCH1 was the most significantly abundant mRNA transcripts in PC3-EMT EVs compared to PC3-Epi EVs. Our results demonstrated that when cells undergo epithelial-to-mesenchymal transition (EMT), a more active loading of cancer progression-related mRNA transcripts may occur. The mRNA cargos of EVs derived from mesenchymal prostate cancer cells may contribute to the pro-EMT function. We found that mRNA transcripts are different in progeny EVs compared to parental cells. EV cargos are not completely reflective of their cell origin, and the underlying mechanism of cargo sorting is complicated and needs to be further elucidated.

Impact of checkpoint blockade on cancer vaccine-activated CD8+ T cell responses

Immune and molecular profiling of CD8 T cells of patients receiving DC vaccines expressing three full-length melanoma antigens (MAs) was performed. Antigen expression levels in DCs had no significant impact on T cell or clinical responses. Patients who received checkpoint blockade before DC vaccination had higher baseline MA-specific CD8 T cell responses but no evidence for improved functional responses to the vaccine. Patients who showed the best clinical responses had low PD-1 expression on MA-specific T cells before and after DC vaccination; however, blockade of PD-1 during antigen presentation by DC had minimal functional impact on PD-1high MA-specific T cells. Gene and protein expression analyses in lymphocytes and tumor samples identified critical immunoregulatory pathways, including CTLA-4 and PD-1. High immune checkpoint gene expression networks correlated with inferior clinical outcomes. Soluble serum PD-L2 showed suggestive positive association with improved outcome. These findings show that checkpoint molecular pathways are critical for vaccine outcomes and suggest specific sequencing of vaccine combinations.