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.

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.

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.

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.