BID expression determines the apoptotic fate of cancer cells after abrogation of the spindle assembly checkpoint by AURKB or TTK inhibitors.

BACKGROUND: Drugs targeting the spindle assembly checkpoint (SAC), such as inhibitors of Aurora kinase B (AURKB) and dual specific protein kinase TTK, are in different stages of clinical development. However, cell response to SAC abrogation is poorly understood and there are no markers for patient selection. METHODS: A panel of 53 tumor cell lines of different origins was used. The effects of drugs were analyzed by MTT and flow cytometry. Copy number status was determined by FISH and Q-PCR; mRNA expression by nCounter and RT-Q-PCR and protein expression by Western blotting. CRISPR-Cas9 technology was used for gene knock-out (KO) and a doxycycline-inducible pTRIPZ vector for ectopic expression. Finally, in vivo experiments were performed by implanting cultured cells or fragments of tumors into immunodeficient mice. RESULTS: Tumor cells and patient-derived xenografts (PDXs) sensitive to AURKB and TTK inhibitors consistently showed high expression levels of BH3-interacting domain death agonist (BID), while cell lines and PDXs with low BID were uniformly resistant. Gene silencing rendered BID-overexpressing cells insensitive to SAC abrogation while ectopic BID expression in BID-low cells significantly increased sensitivity. SAC abrogation induced activation of CASP-2, leading to cleavage of CASP-3 and extensive cell death only in presence of high levels of BID. Finally, a prevalence study revealed high BID mRNA in 6% of human solid tumors. CONCLUSIONS: The fate of tumor cells after SAC abrogation is driven by an AURKB/ CASP-2 signaling mechanism, regulated by BID levels. Our results pave the way to clinically explore SAC-targeting drugs in tumors with high BID expression.

Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection.

Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.

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.

Identification of ALK, ROS1, and RET Fusions by a Multiplexed mRNA-Based Assay in Formalin-Fixed, Paraffin-Embedded Samples from Advanced Non-Small-Cell Lung Cancer Patients.

BACKGROUND: Anaplastic lymphoma receptor tyrosine kinase (ALK), ROS proto-oncogene 1, receptor tyrosine kinase (ROS1), and ret proto-oncogene (RET) fusions are present in 5%-7% of patients with advanced non-small-cell lung cancer (NSCLC); their accurate identification is critical to guide targeted therapies. FISH and immunohistochemistry (IHC) are considered the gold standards to determine gene fusions, but they have limitations. The nCounter platform is a potentially useful genomic tool for multiplexed detection of gene fusions, but has not been validated in the clinical setting. METHODS: Formalin-fixed, paraffin embedded (FFPE) samples from 108 patients with advanced NSCLC were analyzed with an nCounter-based assay and the results compared with FISH, IHC, and reverse transcription PCR (RT-PCR). Data on response to fusion kinase inhibitors was retrospectively collected in a subset of 29 patients. RESULTS: Of 108 FFPE samples, 98 were successfully analyzed by nCounter (91%), which identified 55 fusion-positive cases (32 ALK, 21 ROS1, and 2 RET). nCounter results were highly concordant with IHC for ALK (98.5%, CI = 91.8-99.7), while 11 discrepancies were found compared with FISH (87.5% concordance, CI = 79.0-92.9). For ROS1, nCounter showed similar agreement with IHC and FISH (87.2% and 85.9%), but a substantial number of samples were positive only by 1 or 2 techniques. Of the 25 patients deriving clinical benefit from fusion kinase inhibitors, 24 were positive by nCounter and 22 by FISH. CONCLUSIONS: nCounter compares favorably with IHC and FISH and can be used for identifying patients with advanced NSCLC positive for ALK/ROS1/RET fusion genes.

Combinatory effect of BRCA1 and HERC2 expression on outcome in advanced non-small-cell lung cancer.

BACKGROUND: BRCA1 is a main component of homologous recombination and induces resistance to platinum in preclinical models. It has been studied as a potential predictive marker in lung cancer. Several proteins modulate the function of BRCA1. The E3 ubiquitin ligase HERC2 facilitates the assembly of the RNF8-UBC13 complex to recruit BRCA1 to DNA damage sites. The combined analysis of multiple components of the pathway leading to the recruitment of BRCA1 at DNA damage sites has the potentiality to improve the BRCA1 predictive model. METHODS: We retrospectively analyzed 71 paraffin-embedded tumor samples from advanced non-small-cell lung cancer patients treated with first-line platinum based chemotherapy and measured the mRNA expression levels of BRCA1, RNF8, UBC13 and HERC2 using real-time PCR. The mRNA expression was categorized using median value as cut-off point. RESULTS: The median progression-free survival of all 71 patients was 7.2 months whereas the median overall survival of the study population was 10.7 months. Among patients with low BRCA1 expression, the median PFS was 7.4 months in the presence of low HERC2 levels and 5.9 months for patients expressing high HERC2 levels (p = 0.01). The median OS was 15.3 months for patients expressing low levels of both genes and 7.4 months for those with low BRCA1 but high HERC2 (p = 0.008). The multivariate analysis showed that among patients with Eastern Cooperative Oncology Group performance status 0-1, the combined low expression of both BRCA1 and HERC2 clearly reduced the risk of progression (p = 0.03) and of death (p = 0.004). CONCLUSIONS: These findings confirm the potentiality of integrated DNA repair components analysis in predicting the sensitivity to platinum in lung cancer. The study indicates a predictive role for HERC2 mRNA expression and paves the way for further refinement of the BRCA1 predictive model.

KRAS G12C-mutant driven non-small cell lung cancer (NSCLC).

KRAS G12C mutations in non-small cell lung cancer (NSCLC) partially respond to KRAS G12C covalent inhibitors. However, early adaptive resistance occurs due to rewiring of signaling pathways, activating receptor tyrosine kinases, primarily EGFR, but also MET and ligands. Evidence indicates that treatment with KRAS G12C inhibitors (sotorasib) triggers the MRAS:SHOC2:PP1C trimeric complex. Activation of MRAS occurs from alterations in the Scribble and Hippo-dependent pathways, leading to YAP activation. Other mechanisms that involve STAT3 signaling are intertwined with the activation of MRAS. The high-resolution MRAS:SHOC2:PP1C crystallization structure allows in silico analysis for drug development. Activation of MRAS:SHOC2:PP1C is primarily Scribble-driven and downregulated by HUWE1. The reactivation of the MRAS complex is carried out by valosin containing protein (VCP). Exploring these pathways as therapeutic targets and their impact on different chemotherapeutic agents (carboplatin, paclitaxel) is crucial. Comutations in STK11/LKB1 often co-occur with KRAS G12C, jeopardizing the effect of immune checkpoint (anti-PD1/PDL1) inhibitors.

Vaccine antibodies against a synthetic epidermal growth factor variant enhance the antitumor effects of inhibitors targeting the MAPK/ERK and PI3K/Akt pathways.

BACKGROUND: The EGFR pathway is involved in intrinsic and acquired resistance to a wide variety of targeted therapies in cancer. Vaccination represents an alternative to the administration of anti-EGFR monoclonal antibodies, such as cetuximab or panitumumab. Here, we tested if anti-EGF antibodies generated by vaccination (anti-EGF VacAbs) could potentiate the activity of drugs targeting the ERK/MAPK and PI3K/Akt pathways. METHODS: Non-small cell lung cancer (NSCLC), colorectal cancer (CRC) and melanoma cell lines harboring KRAS, NRAS, BRAF and PIK3CA mutations were used. Anti-EGF VacAbs were obtained by immunizing rabbits with a fusion protein containing a synthetic, highly mutated variant of human EGF. Cell viability was determined by MTT, total and phosphorylated proteins by Western blotting, cell cycle distribution and cell death by flow cytometry and emergence of resistance by microscopic examination in low density cultures. RESULTS: Anti-EGF VacAbs potentiated the antiproliferative effects of MEK, KRAS G12C, BRAF, PI3K and Akt inhibitors in KRAS, NRAS, BRAF and PIK3CA mutant cells and delayed the appearance of resistant clones in vitro. The effects of anti-EGF VacAbs were comparable or superior to those of panitumumab and cetuximab. The combination of anti-EGF VacAbs with the targeted inhibitors effectively suppressed EGFR downstream pathways and sera from patients immunized with an anti-EGF vaccine also blocked activation of EGFR effectors. CONCLUSIONS: Anti-EGF VacAbs enhance the antiproliferative effects of drugs targeting the ERK/MAPK and PIK3CA/Akt pathways. Our data provide a rationale for clinical trials testing anti-EGF vaccination combined with inhibitors selected according to the patient's genetic profile.

Brief Report: circRUNX1 as Potential Biomarker for Cancer Recurrence in EGFR Mutation-Positive Surgically Resected NSCLC.

Introduction: As recently evidenced by the ADAURA trial, most patients with stages IB to IIIA of resected EGFR-mutant lung adenocarcinoma benefit from osimertinib as adjuvant therapy. Nevertheless, predictive markers of response and recurrence are still an unmet need for more than 10% of these patients. Some circular RNAs (circRNAs) have been reported to play a role in tumor growth and proliferation. In this project, we studied circRNA expression levels in formalin-fixed, paraffin-embedded lung tumor samples to explore their biomarker potential and develop a machine learning (ML)-based signature that could predict the benefit of adjuvant EGFR tyrosine kinase inhibitors in patients with EGFR-mutant NSCLC. Methods: Patients with surgically resected EGFR mutant-positive, stages I to IIIB NSCLC were recruited from February 2007 to December 2015. Formalin-fixed, paraffin-embedded tumor samples were retrospectively collected from those patients with a follow-up period of more than or equal to 36 months (N = 76). Clinicopathologic features were annotated. Total RNA was purified and quantified prior nCounter processing with our circRNA custom panel. Data analysis and ML were performed taking into consideration circRNA expression levels and recurrence-free survival (RFS). RFS was defined from the day of surgery to the day when recurrence was detected radiologically or the death owing to any cause. Results: Of the 76 patients with EGFR mutation-positive NSCLC included in the study, 34 relapsed within 3 years after resection. The median age of the relapsing cohort was 71.5 (range: 49-89) years. Most patients were nonsmokers (n = 21; 61.8%) and of female sex (n = 21; 61.8%). Most cases (n = 17; 50%) presented an exon 21 mutation, whereas 15 and four patients had an exon 19 and exon 18 mutation, respectively. Differential expression analysis revealed that circRUNX1, along with circFUT8 and circAASDH, was up-regulated in relapsing patients (p < 0.05 and >2 fold-change). A ML-based circRNA signature predictive of recurrence in patients with EGFR mutation-positive NSCLC, comprising circRUNX1, was developed. Our final model including selected 6-circRNA signature with random forest algorithm was able to classify relapsing patients with an accuracy of 83% and an area under the receiver operating characteristic curve of 0.91.RFS was significantly shorter not only for the subgroup of patients with high versus low circRUNX1 expression but also for the group classified as recurrent by the ML circRNA signature when compared with those classified as nonrecurrent. Conclusions: Our findings suggest that circRUNX1 and the presented ML-developed signature could be novel tools to predict the benefit of adjuvant EGFR tyrosine kinase inhibitors with regard to RFS in patients with EGFR-mutant NSCLC. The training and validation phases of our ML signature will be conducted including bigger independent cohorts.

Gene expression signatures in conjunctival fornix aspirates of patients with dry eye disease associated with Meibomian gland dysfunction. A proof-of-concept study.

BACKGROUND: Meibomian gland dysfunction (MGD) is one of the most common conditions in ophthalmic practice and the most frequent cause of evaporative dry eye disease (DED). However, the immune mechanisms leading to this pathology are not fully understood and the diagnostic tests available are limited. Here, we used the nCounter technology to analyze immune gene expression in DED-MGD that can be used for developing diagnostic signatures for DED. METHODS: Conjunctival cell samples were obtained by aspiration from patients with DED-MGD (n = 27) and asymptomatic controls (n = 22). RNA was purified, converted to cDNA, preamplified and analyzed using the Gene Expression Human Immune V2 panel (NanoString), which includes 579 target and 15 housekeeping genes. A machine learning (ML) algorithm was applied to design a signature associated with DED-MGD. RESULTS: Forty-five immune genes were found upregulated in DED-MGD vs. controls, involved in eight signaling pathways, IFN I/II, MHC class I/II, immunometabolism, B cell receptor, T Cell receptor, and T helper-17 (Th-17) differentiation. Additionally, statistically significant correlations were found between 31 genes and clinical characteristics of the disease such as lid margin or tear osmolarity (Pearson's r < 0.05). ML analysis using a recursive feature elimination (RFE) algorithm selected a 4-gene mRNA signature that discriminated DED-MGD from control samples with an area under the ROC curve (AUC ROC) of 0.86 and an accuracy of 77.5%. CONCLUSIONS: Multiplexed mRNA analysis of conjunctival cells can be used to analyze immune gene expression patterns in patients with DED-MGD and to generate diagnostic signatures.

Detecting ALK, ROS1, and RET fusions and the METΔex14 splicing variant in liquid biopsies of non-small-cell lung cancer patients using RNA-based techniques.

ALK, ROS1, and RET fusions and MET∆ex14 variant associate with response to targeted therapies in non-small-cell lung cancer (NSCLC). Technologies for fusion testing in tissue must be adapted to liquid biopsies, which are often the only material available. In this study, circulating-free RNA (cfRNA) and extracellular vesicle RNA (EV-RNA) were purified from liquid biopsies. Fusion and MET∆ex14 transcripts were analyzed by nCounter (Nanostring) and digital PCR (dPCR) using the QuantStudio® System (Applied Biosystems). We found that nCounter detected ALK, ROS1, RET, or MET∆ex14 aberrant transcripts in 28/40 cfRNA samples from positive patients and 0/16 of control individuals (70% sensitivity). Regarding dPCR, aberrant transcripts were detected in the cfRNA of 25/40 positive patients. Concordance between the two techniques was 58%. Inferior results were obtained when analyzing EV-RNA, where nCounter often failed due to a low amount of input RNA. Finally, results of dPCR testing in serial liquid biopsies of five patients correlated with response to targeted therapy. We conclude that nCounter can be used for multiplex detection of fusion and MET∆ex14 transcripts in liquid biopsies, showing a performance comparable with next-generation sequencing platforms. dPCR could be employed for disease follow-up in patients with a known alteration. cfRNA should be preferred over EV-RNA for these analyses.

Selective isolation of extracellular vesicles from minimally processed human plasma as a translational strategy for liquid biopsies.

BACKGROUND: Intercellular communication is mediated by extracellular vesicles (EVs), as they enclose selectively packaged biomolecules that can be horizontally transferred from donor to recipient cells. Because all cells constantly generate and recycle EVs, they provide accurate timed snapshots of individual pathophysiological status. Since blood plasma circulates through the whole body, it is often the biofluid of choice for biomarker detection in EVs. Blood collection is easy and minimally invasive, yet reproducible procedures to obtain pure EV samples from circulating biofluids are still lacking. Here, we addressed central aspects of EV immunoaffinity isolation from simple and complex matrices, such as plasma. METHODS: Cell-generated EV spike-in models were isolated and purified by size-exclusion chromatography, stained with cellular dyes and characterized by nano flow cytometry. Fluorescently-labelled spike-in EVs emerged as reliable, high-throughput and easily measurable readouts, which were employed to optimize our EV immunoprecipitation strategy and evaluate its performance. Plasma-derived EVs were captured and detected using this straightforward protocol, sequentially combining isolation and staining of specific surface markers, such as CD9 or CD41. Multiplexed digital transcript detection data was generated using the Nanostring nCounter platform and evaluated through a dedicated bioinformatics pipeline. RESULTS: Beads with covalently-conjugated antibodies on their surface outperformed streptavidin-conjugated beads, coated with biotinylated antibodies, in EV immunoprecipitation. Fluorescent EV spike recovery evidenced that target EV subpopulations can be efficiently retrieved from plasma, and that their enrichment is dependent not only on complex matrix composition, but also on the EV surface phenotype. Finally, mRNA profiling experiments proved that distinct EV subpopulations can be captured by directly targeting different surface markers. Furthermore, EVs isolated with anti-CD61 beads enclosed mRNA expression patterns that might be associated to early-stage lung cancer, in contrast with EVs captured through CD9, CD63 or CD81. The differential clinical value carried within each distinct EV subset highlights the advantages of selective isolation. CONCLUSIONS: This EV isolation protocol facilitated the extraction of clinically useful information from plasma. Compatible with common downstream analytics, it is a readily implementable research tool, tailored to provide a truly translational solution in routine clinical workflows, fostering the inclusion of EVs in novel liquid biopsy settings.

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.

Multiplex Analysis of CircRNAs from Plasma Extracellular Vesicle-Enriched Samples for the Detection of Early-Stage Non-Small Cell Lung Cancer.

BACKGROUND: The analysis of liquid biopsies brings new opportunities in the precision oncology field. Under this context, extracellular vesicle circular RNAs (EV-circRNAs) have gained interest as biomarkers for lung cancer (LC) detection. However, standardized and robust protocols need to be developed to boost their potential in the clinical setting. Although nCounter has been used for the analysis of other liquid biopsy substrates and biomarkers, it has never been employed for EV-circRNA analysis of LC patients. METHODS: EVs were isolated from early-stage LC patients (n = 36) and controls (n = 30). Different volumes of plasma, together with different number of pre-amplification cycles, were tested to reach the best nCounter outcome. Differential expression analysis of circRNAs was performed, along with the testing of different machine learning (ML) methods for the development of a prognostic signature for LC. RESULTS: A combination of 500 µL of plasma input with 10 cycles of pre-amplification was selected for the rest of the study. Eight circRNAs were found upregulated in LC. Further ML analysis selected a 10-circRNA signature able to discriminate LC from controls with AUC ROC of 0.86. CONCLUSIONS: This study validates the use of the nCounter platform for multiplexed EV-circRNA expression studies in LC patient samples, allowing the development of prognostic signatures.

mRNA expression levels and genetic status of genes involved in the EGFR and NF-κB pathways in metastatic non-small-cell lung cancer patients.

BACKGROUND: Metastatic non-small-cell lung cancer (NSCLC) has a dismal prognosis. EGFR is overexpressed or mutated in a large proportion of cases. Downstream components of the EGFR pathway and crosstalk with the NF-κB pathway have not been examined at the clinical level. We explored the prognostic significance of the mRNA expression of nine genes in the EGFR and NF-κB pathways and of BRCA1 and RAP80 in patients in whom EGFR and K-ras gene status had previously been determined. In addition, NFKBIA and DUSP22 gene status was also determined. METHODS: mRNA expression of the eleven genes was determined by QPCR in 60 metastatic NSCLC patients and in nine lung cancer cell lines. Exon 3 of NFKBIA and exon 6 of DUSP22 were analyzed by direct sequencing. Results were correlated with outcome to platinum-based chemotherapy in patients with wild-type EGFR and to erlotinib in those with EGFR mutations. RESULTS: BRCA1 mRNA expression was correlated with EZH2, AEG-1, Musashi-2, CYLD and TRAF6 expression. In patients with low levels of both BRCA1 and AEG-1, PFS was 13.02 months, compared to 5.4 months in those with high levels of both genes and 7.7 months for those with other combinations (P=0.025). The multivariate analysis for PFS confirmed the prognostic role of high BRCA1/AEG-1 expression (HR, 3.1; P=0.01). Neither NFKBIA nor DUSP22 mutations were found in any of the tumour samples or cell lines. CONCLUSIONS: The present study provides a better understanding of the behaviour of metastatic NSCLC and identifies the combination of BRCA1 and AEG-1 expression as a potential prognostic model.

Combined FGFR and Akt pathway inhibition abrogates growth of FGFR1 overexpressing EGFR-TKI-resistant NSCLC cells.

EGFR tyrosine kinase inhibitor (TKI) resistance in non-small cell lung cancer (NSCLC) patients is inevitable. Identification of resistance mechanisms and corresponding targeting strategies can lead to more successful later-line treatment in many patients. Using spectrometry-based proteomics, we identified increased fibroblast growth factor receptor 1 (FGFR1) expression and Akt activation across erlotinib, gefitinib, and osimertinib EGFR-TKI-resistant cell line models. We show that while combined EGFR-TKI and FGFR inhibition showed some efficacy, simultaneous inhibition of FGFR and Akt or PI3K induced superior synergistic growth inhibition of FGFR1-overexpressing EGFR-TKI-resistant NSCLC cells. This effect was confirmed in vivo. Only dual FGFR and Akt inhibition completely blocked the resistance-mediating signaling pathways downstream of Akt. Further, increased FGFR1 expression was associated with significantly lower PFS in EGFR-TKI-treated NSCLC patients, and increased FGFR1 were demonstrated in a few post- vs. pre-EGFR-TKI treatment clinical biopsies. The superior therapeutic benefit of combining FGFR and Akt inhibitors provide the rationale for clinical trials of this strategy.

BRCA1 Expression and Outcome in Patients With EGFR-Mutant NSCLC Treated With Gefitinib Alone or in Combination With Olaparib.

INTRODUCTION: DNA repair capacity, as exemplified by BRCA1 gene expression, is related with outcome to EGFR tyrosine kinase inhibitors in patients with EGFR-mutant NSCLC. Olaparib, a PARP inhibitor, reduces BRCA1 expression. Olaparib was tested in combination with gefitinib versus gefitinib single agent, as a first-line therapy for patients with EGFR-mutant NSCLC in the GOAL study (trial registration: NCT01513174). Here, we report the results of the biomarker-related prespecified secondary objectives of the GOAL study. METHODS: We evaluated the impact of BRCA1 mRNA expression in 91 patients with EGFR-mutant NSCLC. Of those 91 patients, 51 were randomized to treatment with gefitinib and 40 were randomized to treatment with gefitinib plus olaparib. We explored in vitro whether BRCA1 mRNA levels are related with outcome to gefitinib plus olaparib. The expression levels of 53BP1, CtIP, and AXL were also explored and correlated with the treatment outcome. RESULTS: Overall, as what happened in the GOAL study, no statistically significant difference was observed in median progression-free survival (PFS) between the two treatment arms, for the 91 patients of the present study (p = 0.2419). For patients with high BRCA1 mRNA expression (BRCA1-high group), median PFS was 12.9 months in the gefitinib plus olaparib arm, compared with 9.2 months in the gefitinib arm (p = 0.0449). In the gefitinib arm, median PFS was 9.1 months for the BRCA1-high group and 10.2 months for the BRCA1-low group (p = 0.0193). We observed a more pronounced synergism of gefitinib plus olaparib in cells with higher BRCA1 compared with those with low BRCA1 mRNA expression. CONCLUSIONS: High BRCA1 mRNA expression identified patients with NSCLC who benefited from gefitinib plus olaparib in the GOAL phase 2 clinical trial.

Analysis of extracellular vesicle mRNA derived from plasma using the nCounter platform.

Extracellular vesicles (EVs) are double-layered phospholipid membrane vesicles that are released by most cells and can mediate intercellular communication through their RNA cargo. In this study, we tested if the NanoString nCounter platform can be used for the analysis of EV-mRNA. We developed and optimized a methodology for EV enrichment, EV-RNA extraction and nCounter analysis. Then, we demonstrated the validity of our workflow by analyzing EV-RNA profiles from the plasma of 19 cancer patients and 10 controls and developing a gene signature to differentiate cancer versus control samples. TRI reagent outperformed automated RNA extraction and, although lower plasma input is feasible, 500 µL provided highest total counts and number of transcripts detected. A 10-cycle pre-amplification followed by DNase treatment yielded reproducible mRNA target detection. However, appropriate probe design to prevent genomic DNA binding is preferred. A gene signature, created using a bioinformatic algorithm, was able to distinguish between control and cancer EV-mRNA profiles with an area under the ROC curve of 0.99. Hence, the nCounter platform can be used to detect mRNA targets and develop gene signatures from plasma-derived EVs.

Comprehensive analysis of the clinicopathological features, targetable profile, and prognosis of mucinous adenocarcinoma of the lung.

PURPOSE: The clinicopathological or genetic features related to the prognosis of mucinous adenocarcinoma are unknown because of its rarity. The clinicopathological or targetable features were investigated for better management of patients with mucinous adenocarcinoma of the lung. METHODS: We comprehensively evaluated the clinicopathological and genetic features of 60 completely resected mucinous lung adenocarcinomas. Targetable genetic variants were explored using nCounter and polymerase chain reaction, PD-L1 and TTF-1 expression were evaluated using immunohistochemistry. We analyzed the prognostic impact using the Kaplan-Meier method and log-rank test. RESULTS: Of the 60 enrolled patients, 13 (21.7%) had adenocarcinoma in situ/minimally invasive adenocarcinoma, and 47 (78.3%) had invasive mucinous adenocarcinoma (IMA). Fifteen patients (25%) showed a pneumonic appearance on computed tomography (CT). CD74-NRG1 fusion, EGFR mutations, and BRAF mutation were detected in three (5%), four (6.7%), and one (1.7%) patient(s), respectively. KRAS mutations were detected in 31 patients (51.7%). Two patients (3.5%) showed immunoreactivity for PD-L1. No in situ or minimally invasive cases recurred. IMA patients with pneumonic appearance had significantly worse recurrence-free survival (RFS) and overall survival (OS) (p < 0.001). Furthermore, IMA patients harboring KRAS mutations had worse RFS (p = 0.211). Multivariate analysis revealed that radiological pneumonic appearance was significantly associated with lower RFS (p < 0.003) and OS (p = 0.012). KRAS mutations served as an unfavorable status for RFS (p = 0.043). CONCLUSION: Mucinous adenocarcinoma had a low frequency of targetable genetic variants and PD-L1 immunoreactivity; however, KRAS mutations were frequent. Pneumonic appearance on CT imaging and KRAS mutations were clinicopathological features associated with a worse prognosis.

Multiplex RNA-based detection of clinically relevant MET alterations in advanced non-small cell lung cancer.

MET inhibitors have shown activity in non-small-cell lung cancer patients (NSCLC) with MET amplification and exon 14 skipping (METΔex14). However, patient stratification is imperfect, and thus, response rates have varied widely. Here, we studied MET alterations in 474 advanced NSCLC patients by nCounter, an RNA-based technique, together with next-generation sequencing (NGS), fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and reverse transcriptase polymerase chain reaction (RT-PCR), exploring correlation with clinical benefit. Of the 474 samples analyzed, 422 (89%) yielded valid results by nCounter, which identified 13 patients (3%) with METΔex14 and 15 patients (3.5%) with very-high MET mRNA expression. These two subgroups were mutually exclusive, displayed distinct phenotypes and did not generally coexist with other drivers. For METΔex14, 3/8 (37.5%) samples positive by nCounter tested negative by NGS. Regarding patients with very-high MET mRNA, 92% had MET amplification by FISH and/or NGS. However, FISH failed to identify three patients (30%) with very-high MET RNA expression, among which one received MET tyrosine kinase inhibitor treatment deriving clinical benefit. Our results indicate that quantitative mRNA-based techniques can improve the selection of patients for MET-targeted therapies.

RNA-Based Multiplexing Assay for Routine Testing of Fusion and Splicing Variants in Cytological Samples of NSCLC Patients.

The detection of ALK receptor tyrosine kinase (ALK), ROS proto-oncogen1, receptor tyrosine kinase (ROS1), ret proto-oncogen (RET), and MET proto-oncogen exon 14 skipping (METΔex14) allows for the selection of specific kinase inhibitor treatment in patients with non-small cell lung cancer (NSCLC). Multiplex technologies are recommended in this setting. We used nCounter, a multiplexed technology based on RNA hybridization, to detect ALK, ROS1, RET, and METΔex14 in RNA purified from cytological specimens (n = 16) and biopsies (n = 132). Twelve of the 16 cytological samples (75.0%) were evaluable by nCounter compared to 120 out of 132 (90.9%) biopsies. The geometrical mean (geomean) of the housekeeping genes of the nCounter panel, but not the total amount of RNA purified, was significantly higher in biopsies vs. cytological samples. Among cytological samples, we detected ALK (n = 3), METΔex14 (n = 1) and very high MET expression (n = 1) positive cases. The patient with METΔex14 had a partial response to tepotinib, one of the patients with ALK fusions was treated with crizotinib with a complete response. Cell blocks and cytological extensions can be successfully used for the detection of fusions and splicing variants using RNA-based methods such as nCounter.