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.

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.

Genes and variants in hematopoiesis-related pathways are associated with gemcitabine/carboplatin-induced thrombocytopenia.

Chemotherapy-induced myelosuppression, including thrombocytopenia, is a recurrent problem during cancer treatments that may require dose alterations or cessations that could affect the antitumor effect of the treatment. To identify genetic markers associated with treatment-induced thrombocytopenia, we whole-exome sequenced 215 non-small cell lung cancer patients homogeneously treated with gemcitabine/carboplatin. The decrease in platelets (defined as nadir/baseline) was used to assess treatment-induced thrombocytopenia. Association between germline genetic variants and thrombocytopenia was analyzed at single-nucleotide variant (SNV) (based on the optimal false discovery rate, the severity of predicted consequence, and effect), gene, and pathway levels. These analyses identified 130 SNVs/INDELs and 25 genes associated with thrombocytopenia (P-value < 0.002). Twenty-three SNVs were validated in an independent genome-wide association study (GWAS). The top associations include rs34491125 in JMJD1C (P-value = 9.07 × 10-5), the validated variants rs10491684 in DOCK8 (P-value = 1.95 × 10-4), rs6118 in SERPINA5 (P-value = 5.83 × 10-4), and rs5877 in SERPINC1 (P-value = 1.07 × 10-3), and the genes CAPZA2 (P-value = 4.03 × 10-4) and SERPINC1 (P-value = 1.55 × 10-3). The SNVs in the top-scoring pathway "Factors involved in megakaryocyte development and platelet production" (P-value = 3.34 × 10-4) were used to construct weighted genetic risk score (wGRS) and logistic regression models that predict thrombocytopenia. The wGRS predict which patients are at high or low toxicity risk levels, for CTCAE (odds ratio (OR) = 22.35, P-value = 1.55 × 10-8), and decrease (OR = 66.82, P-value = 5.92 × 10-9). The logistic regression models predict CTCAE grades 3-4 (receiver operator characteristics (ROC) area under the curve (AUC) = 0.79), and large decrease (ROC AUC = 0.86). We identified and validated genetic variations within hematopoiesis-related pathways that provide a solid foundation for future studies using genetic markers for predicting chemotherapy-induced thrombocytopenia and personalizing treatments.

Treatment patterns and survival outcomes for small-cell lung cancer patients - a Swedish single center cohort study.

Objectives: This real-world study on small-cell lung cancer (SCLC) patients aimed to investigate treatment patterns, outcome of re-challenge with platinum doublet chemotherapy (PDCT), and associations between clinical characteristics and survival outcomes.Material and methods: This retrospective single center cohort study was based on patients diagnosed with SCLC between 2008 and 2016 at the Karolinska University Hospital, Stockholm, Sweden. Patients were divided into two subgroups; limited disease (LD), receiving concomitant chemo- and radiotherapy and extensive disease (ED), receiving palliative PDCT. The progression-free survival (PFS) was defined as the interval between the start of CT and the earliest date of documented progression. 'Refractory relapse' (Rr) and 'Sensitive relapse' (Sr) were defined as relapse occurring < or ≥180 days after start of PDCT, respectively. The results for treatment patterns were reported as numbers and percentages of patients, and descriptive analyses including medians and 95% confidence intervals (CIs). The Cox proportional hazards regression model was applied to assess the relationship between clinical characteristics and overall survival (OS).Results: The study included 544 patients; 408 with ED and 136 patients had LD. The median PFS and OS for ED patients were 5.1 and 7.0, respectively. In the ED subgroup, Sr occurred in 169 patients (41%), with a longer median OS when compared to Rr patients (10.8 vs. 3.6 months). Patients with LD had a median PFS and OS of 12 and 24 months, respectively. Some LD patients did not show a sign of relapse (22%). The majority of LD patients who relapsed had Sr (66%), with a longer median OS when compared to patients with Rr (20.9 vs. 7.8 mo).Conclusions: The survival outcomes for ED and LD SCLC patients correspond to historical data. Patients with Sr after 1st line therapy might benefit from re-challenge with PDCT in the 2nd line setting.

Prognostic factors affecting survival after whole brain radiotherapy in patients with brain metastasized lung cancer.

BACKGROUND: Whole-brain radiotherapy (WBRT) has been the standard of care for multiple NSCLC brain metastases but due to its toxicity and lack of survival benefit, its use in the palliative setting is being questioned. PATIENT AND METHODS: This was a single institution cohort study including brain metastasized lung cancer patients who received WBRT at Karolinska University Hospital. Information about Recursive Partitioning Analysis (RPA) and Graded Prognostic Assessment (GPA) scores, demographics, histopathological results and received oncological therapy were collected. Predictors of overall survival (OS) from the time of received WBRT were identified by Cox regression analyses. OS between GPA and RPA classes were compared by pairwise log rank test. A subgroup OS analysis was performed stratified by RPA class. RESULTS: The cohort consisted of 280 patients. RPA 1 and 2 classes had better OS compared to class 3, patients with GPA <1.5 points had better OS compared to GPA≥ 1.5 points and age >70 years was associated with worse OS (p< .0001 for all comparisons). In RPA class 2 subgroup analysis GPA ≥1.5 points, age ≤70 years and CNS surgery before salvage WBRT were independent positive prognostic factors. CONCLUSIONS: RPA class 3 patients should not receive WBRT, whereas RPA class 1 patients should receive WBRT if clinically indicated. RPA class 2 patients with age ≤70 years and GPA ≥1.5 points should be treated as RPA 1. WBRT should be omitted in RPA 2 patients with age >70. In RPA 2 patients with age ≤70 years and GPA <1.5 points WBRT could be a reasonable option.

miRNA-214 is related to invasiveness of human non-small cell lung cancer and directly regulates alpha protein kinase 2 expression.

The prognosis of non-small cell lung cancer (NSCLC) is poor, since it has often metastasized to distant organs by the time of diagnosis. Therefore, biomarkers predicting metastasis are crucial. miRNAs play important roles in the regulation of different tumor cell processes, including metastasis. We recently showed that miRNA-214 is linked to a radioresistant phenotype of NSCLC. miRNA-214 has been linked to metastasis in other tumor types. Therefore, we examined the role of miRNA-214 in the metastatic potential of NSCLC. We showed that downregulation of miRNA-214 increased invasive potential, and conversely, overexpression of miRNA-214 decreased invasiveness of NSCLC cells in vitro. Gene expression and bioinformatic analyses of NSCLC cells with ablated miRNA-214, identified a number of metastasis-related target genes, including pregnancy-associated plasma protein A (PAPP-A), alpha protein kinase 2 (ALPK2), cyclin-dependent kinase 6 (CDK6) and tumor necrosis-factor alpha-induced protein 3 (TNFAIP3). These were validated on mRNA and protein level to be regulated by miRNA-214. Through immunoprecipitation we showed that only ALPK2 is directly regulated by miRNA-214. We also examined the protein expression of these four genes in NSCLC tumors with respect to metastatic potential. These results showed that NSCLC tumors express these proteins at moderate-high levels in the nucleus, cytoplasm and/or plasma membrane although with no significant correlation to the overall survival or the metastatic potential of the patients. However, we also showed that the membrane-localized PAPP-A had a higher expression level compared to the cytoplasm-localized. In conclusion, we show that low miRNA-214 expression is linked to a higher invasive potential of NSCLC cells.

PD-1 expression in tumor infiltrating lymphocytes as a prognostic marker in early-stage non-small cell lung cancer.

Introduction: Programmed death ligand - 1 (PD-L1) expression is a well-established predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). Programmed death - 1 (PD-1) serves as the target protein to PD-L1 and their interaction serves as a crucial pathway for immune evasion. This study aimed to investigate the expression pattern of PD-1 on Tumor-infiltrating lymphocytes (TILs) in early-stage NSCLC, and its potential role as prognostic biomarker. Materials & methods: PD-1 was evaluated in 474 surgical resected early-stage NSCLC specimens, using Tissue microarray and immunohistochemical staining. Expression was scored as negative (<1%) or positive. Positive PD-1 expression was further divided into low (<10%) and high (≥10%). None of the patients had received treatment with PD-1/PD-L1 inhibitors. Results: PD-1 expression ≥1% in TILs was observed in 83.5% of cases and was associated with pT stage (p=0.02), grade 3 (p=0.004), and adenocarcinoma subtype (p=0.05). Individuals with high PD-1 expression (≥10%) experienced reduced 10-year overall survival (Log-Rank test = 0.005). In addition, high PD-1 expression emerged as an independent factor associated with reduced survival on multivariate analysis (HR: 1.328 (95% CI: 1.074-1.641). Conclusions: Patients with early-stage NSCLC who exhibited PD-1 expression of ≥10% on TILs had an unfavorable 10-year OS rate. These findings indicate that elevated PD-1 expression on TILs can be associated with immune evasion during the early stages of malignancy evolution in the NSCLC setting and further research is required to further delineate the role of PD-1/PD-L1 pathway on tumor immune senescence. These results underline the potential role of PD-1/PD-L1 inhibitors in the treatment of early-stage NSCLC.

Exploring the discrepancies between clinical trials and real-world data: A small-cell lung cancer study.

The potential of real-world data to inform clinical trial design and supplement control arms has gained much interest in recent years. The most common approach relies on reproducing control arm outcomes by matching real-world patient cohorts to clinical trial baseline populations. However, recent studies pointed out that there is a lack of replicability, generalisability, and consensus. In this article, we propose a novel approach that aims to explore and examine these discrepancies by concomitantly investigating the impact of selection criteria and operations on the measurements of outcomes from the patient data. We tested the approach on a dataset consisting of small-cell lung cancer patients receiving platinum-based chemotherapy regimens from a real-world data cohort (n = 223) and six clinical trial control arms (n = 1224). The results showed that the discrepancy between real-world and clinical trial data potentially depends on differences in both patient populations and operational conditions (e.g., frequency of assessments, and censoring), for which further investigation is required. Discovering and accounting for confounders, including hidden effects of differences in operations related to the treatment process and clinical trial study protocol, would potentially allow for improved translation between clinical trials and real-world data. Continued development of the method presented here to systematically explore and account for these differences could pave the way for transferring learning across clinical studies and developing mutual translation between the real-world and clinical trials to inform clinical study design.

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.

Quantitative proteomics profiling of primary lung adenocarcinoma tumors reveals functional perturbations in tumor metabolism.

In this study, we have analyzed human primary lung adenocarcinoma tumors using global mass spectrometry to elucidate the biological mechanisms behind relapse post surgery. In total, we identified over 3000 proteins with high confidence. Supervised multivariate analysis was used to select 132 proteins separating the prognostic groups. Based on in-depth bioinformatics analysis, we hypothesized that the tumors with poor prognosis had a higher glycolytic activity and HIF activation. By measuring the bioenergetic cellular index of the tumors, we could detect a higher dependency of glycolysis among the tumors with poor prognosis. Further, we could also detect an up-regulation of HIF1α mRNA expression in tumors with early relapse. Finally, we selected three proteins that were upregulated in the poor prognosis group (cathepsin D, ENO1, and VDAC1) to confirm that the proteins indeed originated from the tumor and not from a stromal or inflammatory component. Overall, these findings show how in-depth analysis of clinical material can lead to an increased understanding of the molecular mechanisms behind tumor progression.

Validation of the 7th TNM classification for non-small cell lung cancer: a retrospective analysis on prognostic implications for operated node-negative cases.

BACKGROUND: The 7th TNM staging system for non-small cell lung cancer (NSCLC) developed by the International Association for the study of Lung Cancer (IASLC) has been applied in Sweden since the beginning of the year 2010. The aim of this retrospective study was to evaluate the prognostic role of the 7th TNM staging system in a surgical Swedish patient cohort with node-negative NSCLC. MATERIAL AND METHODS: We collected data from stage I patients (pT1-2 pN0, 6th TNM system) who underwent surgery for NSCLC at Karolinska University Hospital from 1987 to 2002. Tumors were restaged according to the 7th TNM version. Cox multivariate survival analysis was implemented in order to determine the prognostic impact of pathological stage when classified according to either the 6th or the 7th TNM systems. RESULTS: The patient population consisted of 452 subjects. Tumor size was ≤ 3 cm in 51% of cases. The predominant histology was adenocarcinoma (53%) and lobectomy was the most common surgical procedure (82% of patients). The five-year survival rate in patients with stage IA vs. IB (6th TNM) was 62% vs. 51%, respectively (log-rank p = 0.036). Corresponding figures for the 7th TNM system were 70% in stage IA-T1a, 51% in stage IA-T1b, 54% in stage IB, 51% in stage IIA and 35% in stage IIB (log-rank p = 0.002). On multivariate analysis, adjusted by age, gender, histology, kind of surgery, grade of differentiation and smoking status, pathological stage was an independent prognostic factor if classified according to the 7th TNM version (p = 0.001), but not if scored according to the 6th TNM edition (p = 0.090). CONCLUSION: The 7th TNM classification system is a more accurate predictor of prognosis in stage I operated patients than the old classification. The new system should be implemented even on retrospective cohorts especially when investigating the prognostic implication of the expression of molecular biomarkers.

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.

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 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.

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.

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.

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.