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.

Insights into EGFR Mutations and Oncogenic KRAS Mutations in Non-Small-Cell Lung Cancer.

Genetic mutations can activate different sets of proto-oncogenes and tumor suppressors genes [...].

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.

Avelumab in Combination With Cetuximab and Chemotherapy as First-Line Treatment for Patients With Advanced Squamous NSCLC.

Introduction: We present the results of a phase 2a trial of first-line avelumab (anti-programmed death-ligand 1 antibody) plus cetuximab (anti-EGFR antibody) in patients with advanced squamous NSCLC. Methods: Patients with recurrent or metastatic squamous NSCLC received avelumab 800 mg (d 1 and 8), cetuximab 250 mg/m2 (d 1) and 500 mg/m2 (d 8), cisplatin 75 mg/m2 (d 1), and gemcitabine 1250 mg/m2 (d 1 and 8) for four 3-week cycles, followed by avelumab 800 mg and cetuximab 500 mg/m2 every 2 weeks. The primary end point was the best overall response; the secondary end points were progression-free survival, duration of response, overall survival, and safety. Efficacy analyses were reported from an updated data cutoff. Results: A total of 43 patients were enrolled. The median follow-up was 6.6 months for the primary analyses and 9.2 months for the efficacy analyses. In the efficacy analyses, 15 patients had a confirmed partial response (objective response rate, 34.9% [95% confidence interval: 21.0%-50.9%]), and the median duration of response was 7.1 months (95% confidence interval: 4.2-12.5 mo). The median progression-free survival and overall survival were 6.1 months and 10.0 months, respectively. In the safety analyses (primary analysis), 38 patients (88.4%) had a treatment-related adverse event, of whom 24 (55.8%) had a grade 3 or higher treatment-related adverse event. Conclusions: The combination of avelumab + cetuximab and chemotherapy showed antitumor activity and tolerable safety; however, the ORR was not improved compared with those reported for current standards of care (NCT03717155).

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.

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.

Prospective analysis of liquid biopsies of advanced non-small cell lung cancer patients after progression to targeted therapies using GeneReader NGS platform.

BACKGROUND: In a significant percentage of advanced non-small cell lung cancer (NSCLC) patients, tumor tissue is unavailable or insufficient for genetic analyses at time to progression. We prospectively analyzed the appearance of genetic alterations associated with resistance in liquid biopsies of advanced NSCLC patients progressing to targeted therapies using the NGS platform. METHODS: A total of 24 NSCLC patients were included in the study, 22 progressing to tyrosine kinase inhibitors and two to other treatments. Liquid biopsies samples were obtained and analyzed using the GeneReadTM QIAact Lung DNA UMI Panel, designed to enrich specific target regions and containing 550 variant positions in 19 selected genes frequently altered in lung cancer tumors. Previously, a retrospective validation of the panel was performed in clinical samples. RESULTS: Of the 21 patients progressing to tyrosine kinase inhibitors with valid results in liquid biopsy, NGS analysis identified a potential mechanism of resistance in 12 (57%). The most common were acquired mutations in ALK and EGFR, which appeared in 8/21 patients (38%), followed by amplifications in 5/21 patients (24%), and KRAS mutations in one patient (5%). Loss of the p.T790M was also identified in two patients progressing to osimertinib. Three of the 21 (14%) patients presented two or more concomitant alterations associated with resistance. Finally, an EGFR amplification was found in the only patient progressing to immunotherapy included in the study. CONCLUSIONS: NGS analysis in liquid biopsies of patients progressing to targeted therapies using the GeneReader platform is feasible and can help the oncologist to make treatment decisions.