Design and Optimization of a Silicon-Based Electrokinetic Microchip for Sensitive Detection of Small Extracellular Vesicles.

Detection of analytes using streaming current has previously been explored using both experimental approaches and theoretical analyses of such data. However, further developments are needed for establishing a viable microchip that can be exploited to deliver a sensitive, robust, and scalable biosensor device. In this study, we demonstrated the fabrication of such a device on silicon wafer using a scalable silicon microfabrication technology followed by characterization and optimization of this sensor for detection of small extracellular vesicles (sEVs) with sizes in the range of 30 to 200 nm, as determined by nanoparticle tracking analyses. We showed that the sensitivity of the devices, assessed by a common protein-ligand pair and sEVs, significantly outperforms previous approaches using the same principle. Two versions of the microchips, denoted as enclosed and removable-top microchips, were developed and compared, aiming to discern the importance of high-pressure measurement versus easier and better surface preparation capacity. A custom-built chip manifold allowing easy interfacing with standard microfluidic connections was also constructed. By investigating different electrical, fluidic, morphological, and fluorescence measurements, we show that while the enclosed microchip with its robust glass-silicon bonding can withstand higher pressure and thus generate higher streaming current, the removable-top configuration offers several practical benefits, including easy surface preparation, uniform probe conjugation, and improvement in the limit of detection (LoD). We further compared two common surface functionalization strategies and showed that the developed microchip can achieve both high sensitivity for membrane protein profiling and low LoD for detection of sEV detection. At the optimum working condition, we demonstrated that the microchip could detect sEVs reaching an LoD of 104 sEVs/mL (when captured by membrane-sensing peptide (MSP) probes), which is among the lowest in the so far reported microchip-based methods.

Application of Process Mining for Modelling Small Cell Lung Cancer Prognosis.

Process mining is a relatively new method that connects data science and process modelling. In the past years a series of applications with health care production data have been presented in process discovery, conformance check and system enhancement. In this paper we apply process mining on clinical oncological data with the purpose of studying survival outcomes and chemotherapy treatment decision in a real-world cohort of small cell lung cancer patients treated at Karolinska University Hospital (Stockholm, Sweden). The results highlighted the potential role of process mining in oncology to study prognosis and survival outcomes with longitudinal models directly extracted from clinical data derived from healthcare.

A Small Molecule Targeting the Intracellular Tyrosine Kinase Domain of ROR1 (KAN0441571C) Induced Significant Apoptosis of Non-Small Cell Lung Cancer (NSCLC) Cells.

The ROR1 receptor tyrosine kinase is expressed in embryonic tissues but is absent in normal adult tissues. ROR1 is of importance in oncogenesis and is overexpressed in several cancers, such as NSCLC. In this study, we evaluated ROR1 expression in NSCLC patients (N = 287) and the cytotoxic effects of a small molecule ROR1 inhibitor (KAN0441571C) in NSCLC cell lines. ROR1 expression in tumor cells was more frequent in non-squamous (87%) than in squamous (57%) carcinomas patients, while 21% of neuroendocrine tumors expressed ROR1 (p = 0.0001). A significantly higher proportion of p53 negative patients in the ROR1+ group than in the p53 positive non-squamous NSCLC patients (p = 0.03) was noted. KAN0441571C dephosphorylated ROR1 and induced apoptosis (Annexin V/PI) in a time- and dose-dependent manner in five ROR1+ NSCLC cell lines and was superior compared to erlotinib (EGFR inhibitor). Apoptosis was confirmed by the downregulation of MCL-1 and BCL-2, as well as PARP and caspase 3 cleavage. The non-canonical Wnt pathway was involved. The combination of KAN0441571C and erlotinib showed a synergistic apoptotic effect. KAN0441571C also inhibited proliferative (cell cycle analyses, colony formation assay) and migratory (scratch wound healing assay) functions. Targeting NSCLC cells by a combination of ROR1 and EGFR inhibitors may represent a novel promising approach for the treatment of NSCLC patients.

Plasma RNA profiling unveils transcriptional signatures associated with resistance to osimertinib in EGFR T790M positive non-small cell lung cancer patients.

Background: Targeted therapy with tyrosine kinases inhibitors (TKIs) against epidermal growth factor receptor (EGFR) is part of routine clinical practice for EGFR mutant advanced non-small cell lung cancer (NSCLC) patients. These patients eventually develop resistance, frequently accompanied by a gatekeeper mutation, T790M. Osimertinib is a third-generation EGFR TKI displaying potency to the T790M resistance mutation. Here we aimed to analyze if exosomal RNAs, isolated from longitudinally sampled plasma of osimertinib-treated EGFR T790M NSCLC patients, could provide biomarkers of acquired resistance to osimertinib. Methods: Plasma was collected at baseline and progression of disease from 20 patients treated with osimertinib in the multicenter phase II study TKI in Relapsed EGFR-mutated non-small cell lung cancer patients (TREM). Plasma was centrifuged at 16,000 g followed by exosomal RNA extraction using Qiagen exoRNeasy kit. RNA was subjected to transcriptomics analysis with Clariom D. Results: Transcriptome profiling revealed differential expression [log2(fold-change) >0.25, false discovery rate (FDR) P<0.15, and P(interaction) >0.05] of 128 transcripts. We applied network enrichment analysis (NEA) at the pathway level in a large collection of functional gene sets. This overall enrichment analysis revealed alterations in pathways related to EGFR and PI3K as well as to syndecan and glypican pathways (NEA FDR <3×10-10). When applied to the 40 individual, sample-specific gene sets, the NEA detected 16 immune-related gene sets (FDR <0.25, P(interaction) >0.05 and NEA z-score exceeding 3 in at least one sample). Conclusions: Our study demonstrates a potential usability of plasma-derived exosomal RNAs to characterize molecular phenotypes of emerging osimertinib resistance. Furthermore, it highlights the involvement of multiple RNA species in shaping the transcriptome landscape of osimertinib-refractory NSCLC patients.

Ras-Related Protein Rab-32 and Thrombospondin 1 Confer Resistance to the EGFR Tyrosine Kinase Inhibitor Osimertinib by Activating Focal Adhesion Kinase in Non-Small Cell Lung Cancer.

Treatment with the tyrosine kinase inhibitor (TKI) osimertinib is the standard of care for non-small cell lung cancer (NSCLC) patients with activating mutations in the epidermal growth factor receptor (EGFR). Osimertinib is also used in T790M-positive NSCLC that may occur de novo or be acquired following first-line treatment with other EGFR TKIs (i.e., gefitinib, erlotinib, afatinib, or dacomitinib). However, patients treated with osimertinib have a high risk of developing resistance to the treatment. A substantial fraction of the mechanisms for resistance is unknown and may involve RNA and/or protein alterations. In this study, we investigated the full transcriptome of parental and osimertinib-resistant cell lines, revealing 131 differentially expressed genes. Knockdown screening of the genes upregulated in resistant cell lines uncovered eight genes to partly confer resistance to osimertinib. Among them, we detected the expression of Ras-related protein Rab-32 (RAB32) and thrombospondin 1 (THBS1) in plasmas sampled at baseline and at disease progression from EGFR-positive NSCLC patients treated with osimertinib. Both genes were upregulated in progression samples. Moreover, we found that knockdown of RAB32 and THBS1 reduced the expression of phosphorylated focal adhesion kinase (FAK). Combination of osimertinib with a FAK inhibitor resulted in synergistic toxicity in osimertinib-resistant cells, suggesting a potential therapeutic drug combination for overcoming resistance to osimertinib in NSCLC patients.

A novel analytical framework for risk stratification of real-world data using machine learning: A small cell lung cancer study.

In recent studies, small cell lung cancer (SCLC) treatment guidelines based on Veterans' Administration Lung Study Group limited/extensive disease staging and resulted in broad and inseparable prognostic subgroups. Evidence suggests that the eight versions of tumor, node, and metastasis (TNM) staging can play an important role to address this issue. The aim of the present study was to improve the detection of prognostic subgroups from a real-word data (RWD) cohort of patients and analyze their patterns using a development pipeline with thoracic oncologists and machine learning methods. The method detected subgroups of patients informing unsupervised learning (partition around medoids) including the impact of covariates on prognosis (Cox regression and random survival forest). An analysis was carried out using patients with SCLC (n = 636) with stage IIIA-IVB according to TNM classification. The analysis yielded k = 7 compacted and well-separated clusters of patients. Performance status (Eastern Cooperative Oncology Group-Performance Status), lactate dehydrogenase, spreading of metastasis, cancer stage, and CRP were the baselines that characterized the subgroups. The selected clustering method outperformed standard clustering techniques, which were not capable of detecting meaningful subgroups. From the analysis of cluster treatment decisions, we showed the potential of future RWD applications to understand disease, develop individualized therapies, and improve healthcare decision making.

Elevated expression of miR-494-3p is associated with resistance to osimertinib in EGFR T790M-positive non-small cell lung cancer.

Background: Non-small cell lung cancer (NSCLC) harboring activating mutations in the gene encoding epidermal growth factor receptor (EGFR) is amenable for targeted therapy with tyrosine kinase inhibitors (TKIs). Eventually, resistance to TKI-therapy occurs resulting in disease progression. A substantial fraction of resistance mechanisms is unknown and may involve alterations in the RNA or protein landscape. MicroRNAs (miRNAs) have been frequently suggested to play roles in various forms of cancer including NSCLC. However, a role of miRNAs in acquired resistance to EGFR TKIs remains elusive. In this work, we aimed to investigate the potential involvement of miRNAs in acquired resistance to the third-generation EGFR TKI osimertinib in NSCLC. Methods: We combined miRNA expression profiling with miRNA-inhibitory screening to identify miRNAs involved in conferring resistance to osimertinib. Finally, we validated our top miRNA candidate by profiling longitudinal plasma exosomal RNA from patients receiving osimertinib as second-line therapy in a clinical trial. Results: Various miRNAs displayed differential expression in parental versus osimertinib-refractory NSCLC cells. miRNA-inhibitory screening revealed miR-494-3p to partially confer resistance to osimertinib in vitro. Expression of miR-494-3p was significantly elevated in plasma sampled at disease progression compared to plasma sampled at treatment baseline in a cohort of 21 EGFR T790M-mutation positive NSCLC patients receiving osimertinib. Conclusions: Our results highlight the need for further therapeutic exploration of miR-494-3p in in vivo models of EGFR-mutant NSCLC.

Cancer Cachexia and Antitumor Immunity: Common Mediators and Potential Targets for New Therapies.

Cancer cachexia syndrome (CCS) is a multifactorial metabolic syndrome affecting a significant proportion of patients. CCS is characterized by progressive weight loss, alterations of body composition and a systemic inflammatory status, which exerts a major impact on the host's innate and adaptive immunity. Over the last few years, the development of immune checkpoint inhibitors (ICIs) transformed the treatment landscape for a wide spectrum of malignancies, creating an unprecedented opportunity for long term remissions in a significant subset of patients. Early clinical data indicate that CCS adversely impairs treatment outcomes of patients receiving ICIs. We herein reviewed existing evidence on the potential links between the mechanisms that promote the catabolic state in CCS and those that impair the antitumor immune response. We show that the biological mediators and processes leading to the development of CCS may also participate in the modulation and the sustainment of an immune suppressive tumor microenvironment and impaired anti-tumor immunity. Moreover, we demonstrate that the deregulation of the host's metabolic homeostasis in cancer cachexia is associated with resistance to ICIs. Further research on the interrelation between cancer cachexia and anti-tumor immunity is required for the effective management of resistance to immunotherapy in this specific but large subgroup of ICI treated individuals.

The Molecular Tumor Board Portal supports clinical decisions and automated reporting for precision oncology.

There is a growing need for systems that efficiently support the work of medical teams at the precision-oncology point of care. Here, we present the implementation of the Molecular Tumor Board Portal (MTBP), an academic clinical decision support system developed under the umbrella of Cancer Core Europe that creates a unified legal, scientific and technological platform to share and harness next-generation sequencing data. Automating the interpretation and reporting of sequencing results decrease the need for time-consuming manual procedures that are prone to errors. The adoption of an expert-agreed process to systematically link tumor molecular profiles with clinical actions promotes consistent decision-making and structured data capture across the connected centers. The use of information-rich patient reports with interactive content facilitates collaborative discussion of complex cases during virtual molecular tumor board meetings. Overall, streamlined digital systems like the MTBP are crucial to better address the challenges brought by precision oncology and accelerate the use of emerging biomarkers.

The association of four genetic variants with myelosuppression in gemcitabine-treated Japanese is not evident in gemcitabine/carboplatin-treated Swedes.

Gemcitabine/carboplatin-induced myelosuppressive adverse drug reactions (ADRs) are clinical problems leading to patient suffering and dose alterations. There is a need for personalised medicine to improve treatment effects and patients' well-being. We tested four genetic variants, rs11141915, rs1901440, rs12046844 and rs11719165, previously suggested as potential biomarkers for gemcitabine-induced leukopenia/neutropenia in Japanese patients, in 213 Swedish gemcitabine/carboplatin-treated non-small cell lung cancer (NSCLC) patients. DNA was genotyped using TaqMan probes and real-time PCR. The relationships between the risk alleles and low toxicity (non-ADR: Common Terminology Criteria for Adverse Events [CTCAE] grades 0) or high toxicity (ADR: CTCAE grades 3-4) of platelets, leukocytes and neutrophils were evaluated using Fisher's exact test. The risk alleles did not correlate with myelosuppression, and the strongest borderline significance (not withstanding adjustment for multiple testing) was for rs1901440 (neutropenia, p = 0.043) and rs11719165 (leukopenia, p = 0.049) where the risk alleles trended towards lower toxicity, contrasting with previous study findings. Risk alleles and higher risk scores were more common among our patients. We conclude that the genetic variants do not apply to Swedish patients treated with gemcitabine/carboplatin. However, they can still be important in other populations and cohorts, especially in a gemcitabine monotherapy setting, where the causal genetic variation might influence myelosuppressive ADRs.

High Density of NRF2 Expression in Malignant Cells Is Associated with Increased Risk of CNS Metastasis in Early-Stage NSCLC.

Nuclear factor erythroid 2-related factor 2 (NRF2) protein expression promotes cancer progression in non-small cell lung cancer (NSCLC). However, its role in the clinical setting has not been established. We retrospectively analyzed data from 304 patients with surgically removed NSCLC. Multiplex antibody staining of NRF2 and thioredoxin reductase 1 (TrxR1) was conducted and scored in cytokeratin-positive (CK+) cells within the whole-tissue core as well as the tumor and stromal compartments of each tissue microarray (TMA) core. A high density of NRF2+/CK+ cells in the whole-tissue core compartment was correlated with a higher risk of central nervous system (CNS) relapse OR = 7.36 (95% CI: 1.64-33.06). The multivariate analysis showed an OR = 8.00 (95% CI: 1.70-37.60) for CNS relapse in NRF2+/CK+ high-density cases. The density of TrxR1+/CK+ cells failed to show any statistically significant risk of relapse. The OS analyses for NRF2+/CK+ and TrxR1+/CK+ cell density failed to show any statistical significance. This is the first study to report a correlation between NRF2+/CK+ cell density and the risk of CNS relapse in early-stage NSCLC. The results of our study may impact the follow-up strategy for early-stage NSCLC patients and eventually improve their prognosis.

Correlation of Clinical Parameters with Intracranial Outcome in Non-Small Cell Lung Cancer Patients with Brain Metastases Treated with Pd-1/Pd-L1 Inhibitors as Monotherapy.

There is a paucity of biomarkers for the prediction of intracranial (IC) outcome in immune checkpoint inhibitor (ICI)-treated non-small cell lung cancer (NSCLC) patients (pts) with brain metastases (BM). We identified 280 NSCLC pts treated with ICIs at Karolinska University Hospital, Sweden, and University Hospital of Heraklion, Greece. The inclusion criteria for response assessment were brain metastases (BM) prior to ICI administration, radiological evaluation with CT or MRI for IC response assessment, PD-1/PD-L1 inhibitors as monotherapy, and no local central nervous system (CNS) treatment modalities for ≥3 months before ICI initiation. In the IC response analysis, 33 pts were included. Non-primary (BM not present at diagnosis) BM, odds ratio (OR): 13.33 (95% CI: 1.424-124.880, p = 0.023); no previous brain radiation therapy (RT), OR: 5.49 (95% CI: 1.210-25.000, p = 0.027); and age ≥70 years, OR: 6.19 (95% CI: 1.27-30.170, p = 0.024) were associated with increased probability of IC disease progression. Two prognostic groups (immunotherapy (I-O) CNS score) were created based on the abovementioned parameters. The I-O CNS poor prognostic group B exhibited a higher probability for IC disease progression, OR: 27.50 (95% CI: 2.88-262.34, p = 0.004). Age, CNS radiotherapy before the start of ICI treatment, and primary brain metastatic disease can potentially affect the IC outcome of NSCLC pts with BM.

Multiplex immune protein profiling of fine-needle aspirates from patients with non-small-cell lung cancer reveals signatures associated with PD-L1 expression and tumor stage.

Biomarker signatures identified through minimally invasive procedures already at diagnosis of non-small-cell lung cancer (NSCLC) could help to guide treatment with immune checkpoint inhibitors (ICI). Here, we performed multiplex profiling of immune-related proteins in fine-needle aspirate (FNA) samples of thoracic lesions from patients with NSCLC to assess PD-L1 expression and identify related protein signatures. Transthoracic FNA samples from 14 patients were subjected to multiplex antibody-based profiling by proximity extension assay (PEA). PEA profiling employed protein panels relevant to immune and tumor signaling and was followed by Qlucore® Omics Explorer analysis. All lesions analyzed were NSCLC adenocarcinomas, and PEA profiles could be used to monitor 163 proteins in all but one sample. Multiple key immune signaling components (including CD73, granzyme A, and chemokines CCL3 and CCL23) were identified and expression of several of these proteins (e.g., CCL3 and CCL23) correlated to PD-L1 expression. We also found EphA2, a marker previously linked to inferior NSCLC prognosis, to correlate to PD-L1 expression. Our identified protein signatures related to stage included, among others, CXCL10 and IL12RB1. We conclude that transthoracic FNA allows for extensive immune and tumor protein profiling with assessment of putative biomarkers of important for ICI treatment selection in NSCLC.

Detection of Tumor-Associated Membrane Receptors on Extracellular Vesicles from Non-Small Cell Lung Cancer Patients via Immuno-PCR.

Precision cancer medicine for non-small-cell lung cancer (NSCLC) has increased patient survival. Nevertheless, targeted agents towards tumor-associated membrane receptors only result in partial remission for a limited time, calling for approaches which allow longitudinal treatment monitoring. Rebiopsy of tumors in the lung is challenging, and metastatic lesions may have heterogeneous signaling. One way ahead is to use liquid biopsies such as circulating tumor DNA or small extracellular vesicles (sEVs) secreted by the tumor into blood or other body fluids. Herein, an immuno-PCR-based detection of the tumor-associated membrane receptors EGFR, HER2, and IGF-1R on CD9-positive sEVs from NSCLC cells and pleural effusion fluid (PE) of NSCLC patients is developed utilizing DNA conjugates of antibody mimetics and affibodies, as detection agents. Results on sEVs purified from culture media of NSCLC cells treated with anti-EGFR siRNA, showed that the reduction of EGFR expression can be detected via immuno-PCR. Protein profiling of sEVs from NSCLC patient PE samples revealed the capacity to monitor EGFR, HER2, and IGF-1R with the immuno-PCR method. We detected a significantly higher EGFR level in sEVs derived from a PE sample of a patient with an EGFR-driven NSCLC adenocarcinoma than in sEVs from PE samples of non-EGFR driven adenocarcinoma patients or in samples from patients with benign lung disease. In summary, we have developed a diagnostic method for sEVs in liquid biopsies of cancer patients which may be used for longitudinal treatment monitoring to detect emerging bypassing resistance mechanisms in a noninvasive way.

Clinicopathological significance of the expression of PD-L1 in non-small cell lung cancer.

INTRODUCTION: PD1/PD-L1 pathway targeting therapies are nowadays an established treatment option for patients with NSCLC. We assessed whether PD-L1 expression in NSCLC tumor cells was associated with specific clinical features or overall survival using four different clones. METHODS AND RESULTS: A retrospective study included formalin-fixed paraffin embedded (FFPE) surgical tumors from 482 patients. PD-L1 status was assessed with immunohistochemistry in tumor cells on tissue microarrays using clones 28-8, 22C3, SP263 and SP142. Associations with OS were assessed by Kaplan-Meier and multivariate Cox's regression analysis. Patients' median age: 68 years (39-86); histology: adenocarcinoma (AdCa) 61%, squamous-cell carcinoma (SqCC) 33%, and large cell carcinoma (LCC) 6%; p-stage: IA (46%), IB (30%), IIA (10%), IIB (11,4%), IIIA (1,2%), IIIB - IV (0,4%). PD-L1 positivity (≥1%) in NSCLC for clones 28-8, 22C3, SP263, SP142 was 41.5%, 34.2%, 42.7%, 10.4%, respectively (Pearson Chi-square p < 0.0001). PD-L1 expression was correlated with histology, tumor size and grading. Statistically significant association between PD-L1 expression and OS in NSCLC and Non-AdCa was observed with clone SP142 (log-rank p = 0.045 and p = 0.05, respectively). Statistically significant association between PD-L1 expression and OS in LCC was observed with clones 22C3 (log-rank p = 0.009) and SP263 (log-rank p = 0.050). CONCLUSIONS: Overexpression of the PD-L1 clone SP142 was associated with poor overall survival in NSCLC and Non-AdCa. Clones 22C3 and SP263 were associated with poor prognosis in LCC. PD-L1 status might serve as a prognostic marker in NSCLC.

Effect of corticosteroids on the outcome of patients with advanced non-small cell lung cancer treated with immune-checkpoint inhibitors.

INTRODUCTION: We analysed patients with advanced non-small cell lung cancer (NSCLC) who were treated with immune-checkpoint inhibitors (ICIs) to address the effect of the timeline and reason for corticosteroid administration on survival outcomes. METHODS: We retrospectively collected clinical data of non-oncogenic driven, advanced NSCLC patients treated with ICIs at Karolinska University Hospital, including the timeline and reason for steroid administration. Steroid administration was defined as > 10 mg prednisolone equivalent for ≥10 days. We subcategorized patients based on the aetiology of steroid administration into three subgroups: a) steroids for supportive reasons but not for cancer palliation; b) steroids for the palliation of cancer-related symptoms; c) steroids for the management of immune-related adverse events (irAEs). Furthermore, to analyse the timeline, patients were categorised into two groups; those who received corticosteroids within 2 weeks before until 2 days after ICI initiation and those who received steroids later during their treatment course. RESULTS: Analysed data from 196 patients showed 46.3% of patients received corticosteroids. Steroid administration due to irAEs did not affect overall survival (OS) (p = 0.38) compared with the steroid naïve group. Only steroid administration for the palliation of cancer-related symptoms was an independent predictor for shorter OS (HR = 2.7; 95% CI, 1.5-4.9). The timeline of steroid administration did not affect OS (p = 0.456) in our cohort. CONCLUSIONS: Steroids due to irAEs do not appear to hamper ICI efficacy. However, the administration of high-dose steroids to palliate malignancy-associated symptoms might reflect the dismal prognosis of this patient group.

A gene expression-based single sample predictor of lung adenocarcinoma molecular subtype and prognosis.

Disease recurrence in surgically treated lung adenocarcinoma (AC) remains high. New approaches for risk stratification beyond tumor stage are needed. Gene expression-based AC subtypes such as the Cancer Genome Atlas Network (TCGA) terminal-respiratory unit (TRU), proximal-inflammatory (PI) and proximal-proliferative (PP) subtypes have been associated with prognosis, but show methodological limitations for robust clinical use. We aimed to derive a platform independent single sample predictor (SSP) for molecular subtype assignment and risk stratification that could function in a clinical setting. Two-class (TRU/nonTRU=SSP2) and three-class (TRU/PP/PI=SSP3) SSPs using the AIMS algorithm were trained in 1655 ACs (n = 9659 genes) from public repositories vs TCGA centroid subtypes. Validation and survival analysis were performed in 977 patients using overall survival (OS) and distant metastasis-free survival (DMFS) as endpoints. In the validation cohort, SSP2 and SSP3 showed accuracies of 0.85 and 0.81, respectively. SSPs captured relevant biology previously associated with the TCGA subtypes and were associated with prognosis. In survival analysis, OS and DMFS for cases discordantly classified between TCGA and SSP2 favored the SSP2 classification. In resected Stage I patients, SSP2 identified TRU-cases with better OS (hazard ratio [HR] = 0.30; 95% confidence interval [CI] = 0.18-0.49) and DMFS (TRU HR = 0.52; 95% CI = 0.33-0.83) independent of age, Stage IA/IB and gender. SSP2 was transformed into a NanoString nCounter assay and tested in 44 Stage I patients using RNA from formalin-fixed tissue, providing prognostic stratification (relapse-free interval, HR = 3.2; 95% CI = 1.2-8.8). In conclusion, gene expression-based SSPs can provide molecular subtype and independent prognostic information in early-stage lung ACs. SSPs may overcome critical limitations in the applicability of gene signatures in lung cancer.

Outcome of Patients with NSCLC and Brain Metastases Treated with Immune Checkpoint Inhibitors in a 'Real-Life' Setting.

There is lack of data addressing the intracranial (IC) efficacy of immune checkpoint inhibitors (ICIs) on brain metastases (BM) in non-small cell lung cancer (NSCLC). This patient category is underrepresented in randomized clinical trials. We retrospectively collected clinical data on patients with non-oncogenic driven NSCLC with BM who were treated with ICIs at two medical oncology institutes in Sweden and Greece from 2016 to 2019. IC efficacy was assessed in patients who had not received local treatment for BM less than three months prior to the initiation of ICIs and had adequate radiological evaluation. We screened 280 patients, of which 51 had BM. BM was an independent predictor for inferior PFS (HR = 2.27; 95% CI, 1.53-3.36) but not OS (HR = 1.58; 95% CI, 0.97-2.60) for the whole patient population. IC response assessment was done on 33 patients. IC objective response rate (ORR) was 24.2%. The presence of neurological symptoms related to BM did not affect IC ORR (p = 0.48). High PD-L1 levels from extracranial biopsies were not a predictive factor for IC ORR (p = 0.13). ICIs are active in NSCLC patients with BM regardless of the presence of neurological symptoms and can achieve durable IC disease stabilization in a subgroup of patients.

The prognostic implications of Notch1, Hes1, Ascl1, and DLL3 protein expression in SCLC patients receiving platinum-based chemotherapy.

OBJECTIVES: The aim was to analyse the tumor expression of Notch1, Hes1, Ascl1, and DLL3 in Small-Cell Lung Cancer (SCLC) and each such biomarker's potential association with clinical characteristics and prognosis after platinum-doublet chemotherapy (PDCT). MATERIAL AND METHODS: The protein expression of the biomarkers was evaluated using immunohistochemistry. Patients were categorized according to their sensitivity to first line PDCT: with a Progression-free survival (PFS) ≥ 3 months after completion of treatment considered "sensitive" and < 3 months after completion of treatment considered "refractory". PFS and overall survival were computed using Kaplan-Meier curves with 95% confidence interval. RESULTS AND CONCLUSION: The study included 46 patients, with 21 and 25 of the patients having "sensitive" and "refractory" disease, respectively. The majority of patients had a high DLL3 expression (n = 38), while a minority had Notch 1-high expression (n = 10). The chi-square test showed that there was a statistically significant negative association between Notch1 and Ascl1 expression (p = 0.013). The overall survival for patients with Notch1- high vs. low expression was 8.1 vs. 12.4 months, respectively (p = 0.036). Notch1 expression was an independent prognostic factor in the multivariate analysis (p = 0.02). No other biomarker showed any prognostic impact in this highly selected SCLC cohort. DLL3 is highly expressed in the majority of advanced staged SCLC cases, as expected. In the same patient population, Notch1 expression might have a potential prognostic implication, by driving a non-neuroendocrine differentiation process. Given the small number of cases with Notch1 high expression, the results of this study needs to be confirmed on a larger cohort.