Pretreatment Non-small Cell Lung Cancer Research Articles

Pretreatment radiomic biomarker for immunotherapy responder prediction in stage IB–IV NSCLC (LCDigital-IO Study): a multicenter retrospective study

BackgroundThe predictive efficacy of current biomarker of immune checkpoint inhibitors (ICIs) is not sufficient. This study investigated the causality between radiomic biomarkers and immunotherapy response status in patients with stage...

Inconsistent CT NSCLC radiomics associated with feature selection methods, predictive models and related factors

Objective. To investigate potential uncertainties in CT-based non-small cell lung cancer (NSCLC) radiomics associated with feature selection methods, predictive models, and their related factors. Approach. CT images from 496 pre-treatment NSCLC patients were retrospectively retrieved from a GE CT scanner. The original patient cohort (100%) was sampled to generate 25%, 50%, and 75% sub-cohorts to investigate potential impact of cohort size. Radiomic features were extracted from the lung nodule using IBEX. Five feature selection methods (analysis of variance, least absolute shrinkage and selection operator, mutual information, minimum redundancy-maximum relevance, Relief) and seven predictive models (DT–decision tree, RF–random forest, LR–logistic regression, SVC–support vector classifier, KNN–k-nearest neighbor, GB–gradient boost, NB–Naïve-Bayesian) were included for the analysis. Cohort size and cohort composition (i.e. same sized cohorts with partially different patients) were investigated as factors related to feature selection methods. The number of input features and model validation methods (2-, 5-, and 10-fold cross-validation) were investigated for predictive models. Using a two-year survival endpoint, AUC values were calculated for the various combinations. Main results. Features ranked by different feature selection methods are not consistent and dependent on cohort size, even for the same methods. Two methods, Relief and LASSO, select 17 and 14 features from 25 common features to all cohort sizes, respectively, while other 3 feature selection methods have <10 features common to all cohort sizes. Feature rankings also highly depend on minor differences in cohort composition. AUCs for the 2100 tested combinations vary from 0.427 to 0.973. Among them, only 16 combinations achieve an AUC > 0.65. There is no clear path to reliable CT NSCLC radiomics. Significance. The use of different feature selection methods and predictive models can generate inconsistent results. This should be further investigated to improve the reliability of radiomic studies.

Pretreatment radiomic biomarker for immunotherapy responder prediction in IB-IV stage NSCLC: A multi-center retrospective study.

e21060 Background: The current biomarker of immune checkpoint inhibitors (ICIs) efficacy is not sufficient. This study investigated the correlation between radiomic biomarker and immunotherapy responder in patients with IB-IV stage non-small-cell lung cancer (NSCLC), including its biological explanation for ICIs treatment response prediction. Methods: CT images from 319 pretreatment NSCLC patients receiving immunotherapy between January, 2015 and November, 2021 were retrospectively collected and were distributed into a discovery (n = 214), independent validation (n = 54), and external test cohort (n = 51). 851 features were extracted from both tumoral and each peri-tumoral VOIs. The reference standard is the durable clinical benefit (DCB) and the crucial exclusion criteria are missing pretreatment CT scans. The predictive value of combined radiomic signature (CRS) was assessed in a cohort of 98 resectable NSCLC patients receiving ICIs. The association of radiomic features and tumor immune landscape on the online dataset (n = 60) was also evaluated. A clinical model was constructed and incorporated with radiomic signature to improve performance further. Results: CRS discriminated between DCB and non-DCB patients in the training cohort (area under the curve (AUC): 0.82, 95% CI: 0.75 to 0.88)) and independent cohort (AUC: 0.75, 95%CI: 0.62 to 0.88). In this study, the predictive value of CRS was better than PD-L1 expression (AUC of PD-L1 subset: 0.59, 95%CI: 0.50 to 0.69) or clinical model (AUC of validation cohort: 0.66, 95%CI: 0.51 to 0.81). When predicting pathological response, CRS divided patients into a major pathological response (MPR) and non-MPR group (AUC: 0.76, 95%CI: 0.67 to 0.81). Moreover, CRS showed a promising stratified ability on overall survival (OS; HR: 0.48, 95%CI: 0.27 to 0.89; p = 0.020) and progression-free survival (PFS; HR: 0.43, 95%CI: 0.26 to 0.74; p = 0.002). Biological pathway analysis on online dataset revealed that dysregulation of Hedgehog and Hippo signaling pathways got involved in the prediction of radiomic features. Conclusions: By analyzing both tumoral and peri-tumoral regions of CT images in a radiomic strategy, we developed a non-invasive biomarker distinguishing responder from ICIs therapy, which might inform clinical decisions on the use of ICIs in advanced as well as resectable NSCLC patients.

Abstract 6768: The potential predictive role of spatial phenotyping in non-small cell lung cancer

Abstract Background Lung cancers are the leading cause of cancer-related deaths with a 5-year-survival of only ~20%. Whilst immunotherapies have led to durable and prolonged survival, only a subset of patients remain responsive. Additional biomarkers are thus needed to better predict if patients will respond or develop resistance against immune checkpoint inhibitor (ICI) therapies. Spatial phenotyping of the tumor microenvironment (TME) is now recognized as a proxy for ICI therapy outcomes. Our study employs an end-to-end spatial biology strategy to survey non-small-cell lung cancer (NSCLC) tissues for new biomarkers that could guide immunotherapy treatments. Methods We phenotyped pre-treatment biopsies from non-small-cell lung cancer (NSCLC) patients treated with single-agent Nivolumab. We first performed 57-plex whole-slide Single Cell Spatial Phenotyping on the PhenoCycler®-Fusion platform. Next, we developed the spatial analysis of a larger NSCLC cohort using customizable PhenoCode Signature Panels (PSP) for high-throughput immune profile (CD3/CD8/CD20/CD68/PanCK + CD4 add-in) and immuno-contexture (CD8/CD68/PD-L1/FoxP3/PanCK + PD-1 add-in) imaging. The PSP panel content combines the barcode-based antibody chemistry from the PhenoCycler platform with the signal amplification of Opal chemistry from the PhenoImager platform. PSP panels were profiled across n=27 NSCLC biopsies and provided a wider breadth of tissue profiling. Results Our whole-slide single-cell spatial phenotyping analyses revealed high phenotypic diversity in the TME of patients responsive and resistant to ICI therapy. However, higher-throughput analyses of the same tissues using targeted PSP panels revealed no significant differences in quantities of immune cell lineages, including T-cells and macrophages. On the contrary, we discovered multiple quantifiable and statistically significant spatial signatures that appear to be predictive of treatment benefit, which confirms the potential biomarker value of spatial associations in patient tissues. Conclusions This study amounts to a uniquely comprehensive Single Cell Spatial Phenotyping analysis of pre-treatment NSCLC biopsies from a single-agent Nivolumab study. Our data catalogue the diversity in the immune microenvironment of NSCLC but highlighted that immune cell quantification is insufficient to stratify patient cohorts. Single-cell spatial phenotyping, on the other hand, promises to reveal new biomarkers that may aid in better stratification of patients in pre-treatment evaluations. Citation Format: Ning Ma, Aditya Pratapa, James Monkman, Ken O’Byrne, Oliver Braubach, Arutha Kulasinghe. The potential predictive role of spatial phenotyping in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6768.

Comparison of the tumor immune microenvironment and checkpoint blockade biomarkers between stage III and IV non-small cell lung cancer

BackgroundAdjuvant immune checkpoint blockade (ICB) following chemoradiotherapy and adding ICB to chemotherapy have been key advances for stages III-IV non-small cell lung cancer (NSCLC) treatment. However, known biomarkers like PD-L1 are not consistently indicative of ICB response. Other markers within the tumor immune microenvironment (TIME) may better reflect ICB response and/or resistance mechanisms, but an understanding of how TIMEs differ between stage III and IV NSCLC has not been explored.MethodsReal-world data from unresectable, stage III-IV, non-squamous, pretreatment NSCLCs (stage III n = 106, stage IV n = 285) were retrospectively analyzed. PD-L1 immunohistochemistry (IHC) was compared to CD274 gene expression. Then, differential gene expression levels, pathway enrichment, and immune infiltrate between stages were calculated from whole-transcriptome RNA-seq. Analyses were stratified by EGFR status.ResultsPD-L1 IHC and CD274 expression in tumor cells were highly correlated (n = 295, P < 2.2e-16, ⍴ = 0.74). CTLA4 expression was significantly increased in stage III tumors (P = 1.32e-04), while no differences were observed for other ICB-related genes. Metabolic pathway activity was significantly enriched in stage IV tumors (P = 0.004), whereas several immune-related KEGG pathways were enriched in stage III. Stage IV tumors had significantly increased macrophage infiltration (P = 0.0214), and stage III tumors had a significantly higher proportion of CD4 + T cells (P = 0.017). CD4 + T cells were also relatively more abundant in EGFR-mutant tumors vs. wild-type (P = 0.0081).ConclusionDirectly comparing the TIMEs of stage III and IV NSCLC, these results carry implications for further studies of ICB response in non-resectable stage III NSCLC and guide further research of prognostic biomarkers and therapeutic targets.

Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer.

BackgroundThe value of plasma threonine, cysteine, and piperonamide as diagnostic biomarkers for non-small cell lung cancer (NSCLC) has been rarely explored. The lack of a validation set containing confounders is common to most previous metabolomics studies. The purpose of this study was to explore and validate the value of plasma amino acids and piperonamide as diagnostic biomarkers for NSCLC using liquid chromatography-tandem mass spectrometry (LC-MS/MS).MethodsA total of 250 participants were included in this study, including 167 patients with pathologically confirmed NSCLC and 83 healthy controls (HCs). These participants were divided into training set, validation set 1, and validation set 2 in chronological order and in a certain proportion. The plasma levels of 22 amino acids and 1 piperonamide in these pre-treatment NSCLC patients and HCs were measured by LC-MS/MS. Metabolic biomarkers were identified after multivariate analysis, univariate analysis, receiver operating characteristic (ROC) analysis. Furthermore, these biomarkers and transcriptomic data were subjected to joint pathway analysis.ResultsThe area under the ROC curve (AUC) values for threonine, piperonamide, arginine, alanine, cysteine, methionine, and histidine in the integrated data set were 0.911, 0.848, 0.909, 0.869, 0.786, 0.597 and 0.637, respectively. This panel composed of these 7 metabolites showed good diagnostic capability for NSCLC (the AUC of this diagnostic panel in each data set was greater than 0.9). The specificity of this diagnostic panel in validation set 2, which included confounders, was 0.970, similar to that of the other datasets. The presence of confounding factors had little effect on the diagnostic accuracy of this panel. The ROC analysis of this diagnostic panel between all stage I NSCLC patients and HCs showed AUC, sensitivity, and specificity of 1.000, 1.000, and 0.988, respectively. Moreover, PSAT1, SHMT2, AOC3, and MAOB were found to be involved in the metabolism of threonine and cysteine.ConclusionsPlasma amino acids and piperonamide have potential as diagnostic biomarkers in NSCLC. This metabolic biomarker panel appears useful for the diagnosis and screening of NSCLC. In addition, metabolomic and transcriptomic integration pathway analysis may help elucidate the mechanism of NSCLC occurrence and development and even reveal new treatment vulnerabilities.

Abstract 3194: Immune biomarkers in the tumor microenvironment associated with response in pre-treatment non-small cell lung cancer (NSCLC) samples with second line immunotherapy follow-up data

Abstract Surgical first line resection samples are frequently accessed to select patients for immune checkpoint inhibitor (ICI) therapy, often based on expression of PD-L1 measured by immunohistochemistry (IHC). However, while PD-L1 expression may enrich for response to ICIs, other immune parameters in the tumor microenvironment will likely contribute to outcome. To assist in the identification of biomarker(s) that might predict response to ICIs, we have analyzed a cohort of pre-treatment NSCLC cases for which second line immunotherapy clinical follow-up data are available. Formalin fixed paraffin embedded (FFPE) tumor samples were analysed (i) by single-plex IHC for CD3, CD8, CD68, CD163 and PD-L1, plus digital image analysis (CellProfilerTM), and (ii) profiled for multidimensional biomarkers using the targeted RNA sequencing and machine-learning platform ImmunoPrism® from Cofactor Genomics. Clinical follow-up data indicated objective response to ICI therapy for 4/18 patients, with average time from initial diagnosis to ICI treatment of 33.5 ± 29.6 months (mean ± SD). While CD68+ macrophage frequencies evaluated by IHC did not differ significantly between responder and non-responder populations, significant increases in T cell numbers (CD3: 2.3-fold; CD8: 2.7-fold; both p&amp;lt;0.05) were observed for the responder population. CD8 T cells were orthogonally measured using the ImmunoPrism assay, and the same significant differences for CD8 were observed. Although a trend towards decreased M2-like CD163+ macrophage/monocyte numbers was apparent by IHC for responders, this was not supported by the Cofactor analysis. When sections from the same FFPE block are analyzed across multiple commercially available platforms, there is high confidence for those signals which show concordance between platforms, such as the increase in CD8 T cell abundance observed for responders in this study. Moving beyond single-analyte biomarkers, a multidimensional biomarker combining immune escape genes and RNA-based immune cell measurements was generated using the ImmunoPrism platform with standard parameters. The resulting biomarker had the following performance characteristics: predictive accuracy, 89%; positive predictive value (PPV), 100%; negative predictive value (NPV), 88%; sensitivity, 50%; and specificity, 100%. A receiver-operating characteristic (ROC) curve was also generated for this putative biomarker, with an area under the curve (AUC) of 0.87. The promising results from this exploratory sample set warrant further investigation in a larger cohort. These data also demonstrate that clinical archives with well-curated demographic and outcome data, such as the FFPE samples analyzed here, provide excellent cohorts for biomarker screening and discovery studies. The application of new multianalyte approaches enables additional signals from the tumor microenvironment to be captured and included for predicting patient response. Citation Format: Milan Bhagat, Woo Ho Kim, Lorenzo Memeo, Lorenzo Colarossi, Natalie LaFranzo, Steve Daniel, Christopher Womack, Marie Cumberbatch. Immune biomarkers in the tumor microenvironment associated with response in pre-treatment non-small cell lung cancer (NSCLC) samples with second line immunotherapy follow-up data [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3194.

Interim subgroup analysis for response by PD-L1 status of CLASSICAL-Lung, a phase Ib/II study of pepinemab (VX15/2503) in combination with avelumab in advanced NSCLC.

3011 Background: Antibody blockade of semaphorin 4D (SEMA4D, CD100) promotes tumoral dendritic cell and CD8+ T cell infiltration and reduces function and recruitment of immunosuppressive myeloid cells. Importantly, these mechanisms to overcome immune exclusion and suppression have been shown to complement immune checkpoint therapies in preclinical models. Pepinemab is an IgG4 humanized monoclonal antibody targeting semaphorin 4D. The CLASSICAL-Lung clinical trial tests the combination of pepinemab with avelumab to couple T cell activation via checkpoint inhibition with beneficial modifications of the immune microenvironment via pepinemab. Methods: This phase 1b/2, single arm, first-in-human study is designed to evaluate the safety, tolerability and efficacy of pepinemab with avelumab in 62 patients (pts) with advanced (stage IIIB/IV) non-small cell lung cancer (NSCLC), including immunotherapy-naïve (ION) pts and pts whose tumors progressed following immunotherapy (IOF). Results: Among 21 evaluable ION pts, 5 experienced partial response (PR), 3 pts had clinical benefit ≥ 1 year, and the disease control rate (DCR) is 81%. Pts enrolled in this study were observed to have lower PD-L1 expression relative to prior single agent studies (likely due to approval of pembrolizumab for first line therapy). We, therefore, performed subgroup analysis for response by PD-L1 status. The objective tumor response (ORR) in the PD-L1 negative and low population ( &lt; 80% TPS by Dako 73-10 assay) appears to be approximately 2-2.5 fold greater with combination therapy than with historical single agent immune checkpoint controls. Notably, 97% of pts who experienced PR or SD were reported to have tumors with negative or low PD-L1 expression. Among 29 evaluable IOF pts, the combination resulted in 59% DCR, including 2 PR and 7 patients with durable clinical benefit of ≥ 23 weeks. Biomarker analysis of pre- and on-treatment biopsies confirmed increased CD8+ T cell density correlating with response. Surprisingly, analysis of myeloid-derived suppressor cells (MDSCs) revealed a relative paucity of these cells in pretreatment NSCLC biopsies as compared to other cancer indications such as HNSCC. Conclusions: This trial is nearing completion with only 5 of 62 subjects remaining on study. Preliminary data suggest the combination is well tolerated and shows signs of increased antitumor activity, particularly in PD-L1 negative or low tumors. Updated clinical response data and immunophenotypic analyses will be presented. Clinical trial information: NCT03268057 .

Genetic alterations in epidermal growth factor receptor-tyrosine kinase inhibitor-naïve non-small cell lung carcinoma.

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) are an approved first-line therapy against unresectable or advanced non-small cell lung cancer (NSCLC) harboring EGFR gene activating mutations. However, the majority of tumors develop acquired resistance against EGFR-TKIs and some tumors exhibit natural resistance. A number of resistance mechanisms against the latest third-generation EGFR-TKIs have been reported, including tertiary EGFR C797S mutation and several gene alterations activating EGFR or other signaling pathways. The current study aimed to identify the frequency of natural EGFR-TKI resistance in pretreatment NSCLC and to predict the therapeutic effect of EGFR-TKIs. A total of 246 EGFR-TKI-naïve NSCLC patients harboring known EGFR gene mutations were identified. The presence of EGFR C797S and T790M mutations were determined using the peptide nucleic acid-locked nucleic acid PCR clamp method. ERBB2, MET, EGFR, ALK, BRAF, FGFR1, MYC, RET, CCND1, CCND2, CDK4, CDK6, MDM2 and MDM4 gene amplification, which can lead to resistance against any generation EGFR-TKIs, was determined using the multiplex ligation-dependent probe amplification assay. No concurrent C797S mutation with known EGFR mutations were identified. T790M mutation was identified in 12 patients (4.9%). ERBB2 or MET gene amplification was found in some patients (0.0-0.4%). MDM2 gene amplification was associated with tumor recurrence and shorter progression-free survival (PFS) for first- or second-generation EGFR-TKIs. De novo EGFR C797S mutation was not identified. Other resistance mechanisms against EGFR-TKIs were indicated in some patients with EGFR-TKI-naïve NSCLC. MDM2 gene amplification, which can lead to altered cell cycle, was associated with tumor recurrence and shorter PFS in EGFR-TKI therapy.

Immune microenvironment composition in non-small cell lung cancer and its association with survival.

ObjectivesIn non‐small cell lung cancer (NSCLC), the immune system and possibly its composition affect survival. In this in silico study, the immune infiltrate composition in NSCLC patients was evaluated.MethodsGene expression data of tumors from early NSCLC patients were obtained from Gene Expression Omnibus (GEO). With CIBERSORT, 22 immune cell fractions were estimated.ResultsThe immune infiltrate of 1430 pretreatment NSCLC patients contained mostly plasma cells, macrophages and CD8 T cells. Higher fractions of resting mast and CD4 T‐helper cells were associated with longer overall survival (OS) (HR = 0.95, P < 0.01; HR = 0.98, = 0.04, respectively) and higher fractions of M2 macrophages and active dendritic cells with shorter survival (HR = 1.02, P = 0.03; HR = 1.03, P = 0.05, respectively). Adenocarcinoma patients with survival data (n = 587) showed higher fractions of resting mast and resting CD4 T cells, and lower M0 macrophages than squamous cell carcinoma (n = 254), which were associated with OS (HR = 0.95, P = 0.04; HR = 0.97, P = 0.01; HR = 1.03, P = 0.01, respectively). Fractions of memory B cells, naïve CD4 T cells and neutrophils had different associations with survival depending on the subtype. Smokers had had higher fractions of regulatory T cell, follicular helper T cell, neutrophil and M2 macrophage, which were associated with shorter survival (HR = 1.3, P < 0.01; HR = 1.13, P = 0.02; HR = 1.09, P = 0.03; HR = 1.04, P = 0.02, respectively).ConclusionPretreatment differences in immune cell composition in NSCLC are associated with survival and depend on smoking status and histological subtype. Smokers' immune composition is associated with lower survival.

Analysis of the immune microenvironment in pre-treatment non-small cell lung cancer (NSCLC) patients with follow-up response data to second-line immunotherapy

Abstract Background Patients selected based on PD-L1 expression for second-line immune checkpoint inhibitor (ICI) treatment are often identified using archival specimens collected months or years prior to starting immunotherapy. Such patients may have received and failed multiple lines of standard of care (SOC) treatments with subsequent potential impact on PD-L1 expression and immune microenvironment. Methods We have analysed formalin fixed paraffin embedded (FFPE) tissues in a cohort of NSCLC patients (n = 16) taken during resection performed as first-line surgical treatment for which radiotherapy, SOC chemotherapy, and second-line immunotherapy clinical follow-up data are available. The immune microenvironment was evaluated by immunohistochemistry (IHC) plus digital image analysis for CD3, CD8, PD-L1, CD68 and CD163, and by Nanostring using the IO360TM gene expression panel, with the aim of exploring whether immune signatures predictive of response to ICI therapy may be identified in such samples. Results Clinical follow-up data indicated objective response to ICI therapy for 4/16 patients (n = 2 Nivolumab, n = 1 Pembrolizumab, n = 1 Durvalumab) with time from first diagnosis to receiving second-line ICI treatment ranging from 5 to 102 (mean 33.6) months. During this time these patients received various lines of radiotherapy and SOC chemotherapy prior to receiving immunotherapy. While the Tumor Inflammation Signature was not predictive of response, gene expression analysis did identify several signatures associated significantly with response, including increased abundance of CD8 T cells, cytotoxic cells, cytotoxicity, MHC class II antigen presentation and Melanoma-Associated Antigens (MAGE). These data were supported by a significant elevation of CD8 T cells by IHC in the responder versus non-responder populations, from a mean of 329 to 961 CD8+ T cells/mm2. Conclusion Taken together these data demonstrate that despite various lines of previous radiotherapy and chemotherapy spanning several years, immune profiles associated with response to second-line immunotherapy can be detected in surgical first-line resection samples. Legal entity responsible for the study The authors. Funding Has not received any funding. Disclosure M. Bhagat: Shareholder / Stockholder / Stock options, Officer / Board of Directors: TriStar Technolgoy Group. All other authors have declared no conflicts of interest.

Coexistence of sensitive and resistant epidermal growth factor receptor (EGFR) mutations in pretreatment non-small cell lung cancer (NSCLC) patients: First or third generation tyrosine kinase inhibitors (TKIs)?

ObjectivesOccasionally, primary 20 T790M/insertion plus sensitive mutations can be detected within a single tumor sample by routine molecular testing, but the optimal clinical management for these patients is unclear. Herein, we determined the optimal treatment strategy for these patients. Materials and methodsFrom January 2011 to January 2017, patients diagnosed with epidermal growth factor receptor (EGFR) mutation were screened. For these harboring primary 20 T790M/insertion plus sensitive mutations, the effectiveness of the first or third generation tyrosine kinase inhibitors (TKIs) were retrospectively analyzed. Results16,842 individuals were screened during the study period with 5900 positive patients identified. Sixty-one patients were confirmed to have primary 20 T790M/insertion plus sensitive mutations (1% of all EGFR-mutant patients, 95% CI, 0.8%–1.3%). Among them, 31 eligible patients were included for survival analyses. The median progression–free survival (PFS) of the 15 osimertinib–treated patients was 18.0 months (95% CI, 15.1–20.9 months), which was greatly longer than the 16 patients who were treated with first generation TKIs (1.2 months, 95% CI, 0.9–1.6, P < 0.001). Similar results were also observed in overall survival (OS) with 25.1 months (95% CI, not calculable) in the osimertinib group and 17.3 months (95% CI, 9.3–25.4 months) in the first generation TKI group (P = 0.02). ConclusionsFor patients harboring primary resistant and sensitive mutations detected by routine clinical methods, first generation TKIs are ineffective even with the presence of sensitive mutations. However, osimertinib shows great survival benefit, and thus, should be considered during the whole clinical management.

Coexistence of EGFR T790M mutation and common activating mutations in pretreatment non-small cell lung cancer: A systematic review and meta-analysis

ObjectivePrevious studies have indicated that EGFR exon 19 deletions in non-small cell lung cancer (NSCLC) are associated with better outcomes to tyrosine kinase inhibitors (TKIs) than the L858R mutation. This study aimed to evaluate whether T790M, a resistant mutation, is more likely to coexist with L858R mutation than with exon 19 deletions in pretreatment NSCLC patients. Materials and methodWe searched MEDLINE and EMBASE up to Nov 30th, 2015 to identify randomized controlled trials (RCTs) and observational studies that reported pretreatment T790M and EGFR-activating mutation. A meta-analysis was performed using a random-effects model. The primary outcome was odds ratio (OR) of pretreatment T790M mutation in NSCLC co-existing with L858R mutation and exon 19 deletions. Stratified analysis was performed based on sensitivity of mutation detection methods for T790M. ResultsWe identified 15 observational studies and 3 RCTs for analysis. Pretreatment T790M was more frequent in L858R than in exon 19 mutated patients. The association of T790M and L858R was statistically significant in observational studies (OR, 1.65, 95% CI, 1.17–2.32), with less precision in RCTs (OR, 1.84, 95% CI, 0.96–3.52). In the stratified analysis based on the sensitivity of the mutation detection methods, the association was observed in the studies using intermediately (detection limit <5% and ≥0.1%; OR, 2.23, 95% CI, 1.19–4.17) and highly sensitive methods (detection limit <0.1%; OR, 1.74, 95% CI, 1.10–2.73), but not in those using low sensitivity methods (detection limit >5%; OR, 1.28, 95% CI, 0.74–2.23). ConclusionsPretreatment EGFR T790M mutation is more likely to coexist with L858R mutation than with exon 19 deletions in NSCLC. This association was observed only in studies using sensitive mutation detection methods (<5%).

Detection of low-level EGFR T790M mutation in lung cancer tissues

Epidermal growth factor receptor (EGFR) gene mutation status is critical to predicting responsiveness to EGFR tyrosine kinase inhibitor (TKI) therapies in non-small cell lung cancer (NSCLC) patients. However, a vast majority of the patients experience recurrence of the cancers by a secondary mutation of EGFR (T790M). Earlier studies suggested evidence that subclones bearing EGFR T790M mutation pre-exist in NSCLCs even prior to the therapies. However, to date, the status of T790M mutation in primary NSCLC is largely known. In this study, we developed an assay using peptide nucleic acid (PNA)-clamping PCR for detection of low-level EGFR T790M mutation. We found that the assay showed the highest sensitivity (0.01% mutation detection) in the clamping condition. We analyzed 147 NSCLC tissues [70 adenocarcinomas (AD), 62 squamous cell carcinomas (SQ), 12 large cell carcinomas (LC), and three adenosquamous carcinomas] that had not been exposed to the TKI therapies, and found 12 (8.2%; 12/147) EGFR T790M mutation in eight AD (11.4%), three SQ (4.8%), and one LC (8.3%) by the PNA-clamping PCR. However, this mutation was not detected by conventional DNA sequencing. Our data indicate that EGFR T790M exists in pretreatment NSCLC at low levels irrespective of histologic types. This study provides a basis for developing an applicable protocol for detecting low-level EGFR T790M mutation in primary NSCLC, which might contribute to predicting recurrence of the tumor in response to the TKI therapies.

Possibility of multivariate function composed of plasma amino acid profiles as a novel screening index for non-small cell lung cancer: a case control study

BackgroundThe amino-acid balance in cancer patients often differs from that in healthy individuals, because of metabolic changes. This study investigated the use of plasma amino-acid profiles as a novel marker for screening non-small-cell lung cancer (NSCLC) patients.MethodsThe amino-acid concentrations in venous blood samples from pre-treatment NSCLC patients (n = 141), and age-matched, gender-matched, and smoking status-matched controls (n = 423), were measured using liquid chromatography and mass spectrometry. The resultant study data set was subjected to multiple logistic regression analysis to identify amino acids related with NSCLC and construct the criteria for discriminating NSCLC patients from controls. A test data set derived from 162 patients and 3,917 controls was used to validate the stability of the constructed criteria.ResultsThe plasma amino-acid profiles significantly differed between the NSCLC patients and the controls. The obtained model (including alanine, valine, isoleucine, histidine, tryptophan and ornithine concentrations) performed well, with an area under the curve of the receiver-operator characteristic curve (ROC_AUC) of >0.8, and allowed NSCLC patients and controls to be discriminated regardless of disease stage or histological type.ConclusionsThis study shows that plasma amino acid profiling will be a potential screening tool for NSCLC.

Performance characteristics of an automated assay for the quantitation of CYFRA 21-1 in human serum

Objectives A fragment of cytokeratin 19, CYFRA 21-1, has been reported to be a sensitive tumor marker for non-small cell lung cancer (NSCLC). We describe analytical performance characteristics of a novel CYFRA 21-1 assay and hypothesize that CYFRA 21-1 complements the clinical sensitivity of carcinoembryonic antigen (CEA) and squamous cell carcinoma antigen (SCCa). Design and methods Performance characteristics of a CYFRA 21-1 immunochemiluminescent assay included analytical sensitivity, imprecision, linearity, analyte stability, and reference interval determination. Ninety-two pretreatment NSCLC serum samples were tested for CYFRA 21-1, CEA, and SCCa. Sensitivity was determined for each marker individually and in combination, with regard to tumor stage and histology. Results The analytical sensitivity was 0.01 ng/mL. Total imprecision ranged from 4.0 to 6.3% at 4.9 to 28.4 ng/mL, respectively. The assay was linear from 0.9 to 71.4 ng/mL (slope = 0.995, intercept = − 0.60, r 2 = 0.999). CYFRA 21-1 was stable for 48 h at ambient temperature and 14 days at 4 °C. The 97.5th percentile of a reference population was 1.9 ng/mL. Across disease stage, the sensitivities of CYFRA 21-1, CEA, and SCCa were 17–81%, 30–52%, and 24–39%, respectively. CYFRA 21-1 combined with CEA or SCCa increased sensitivity above that of any single marker. Conclusions An immunochemiluminescent assay for CYFRA 21-1 had favorable performance characteristics. CYFRA 21-1 was complementary to CEA and SCCa and increased clinical sensitivity in patients with NSCLC.

High-dose radiotherapy in trimodality treatment of Pancoast tumors results in high pathologic complete response rates and excellent long-term survival

We sought to study the clinical characteristics and outcomes of patients treated with a surgery-inclusive multimodality approach for Pancoast tumors. Clinical records of patients with Pancoast lung cancer who were enrolled for multimodality treatment between 1993 and 2003 at our institution were reviewed retrospectively. Thirty-six patients completed neodjuvant chemoradiation followed by en bloc surgical resection, whereas one patient received high-dose radiation alone followed by surgical intervention. There were 22 men and 15 women. Thirty-four lobectomies and 3 pneumonectomies were performed. Pretreatment non-small cell lung cancer stages were IIB, IIIA, IIIB, and IV (presenting with solitary brain metastasis) in 18, 8, 6, and 5 cases, respectively. R0 resection was achieved in 36 (97.3%) patients. Operative mortality was 2.7% (n = 1). High-dose radiotherapy was successfully tolerated in all but 1 patient. Mean total radiation dose was 56.9 Gy. Pathologic complete response was found in 40.5% (n = 15) of patients. Recurrences were found in 50% (n = 18) of patients. Brain metastasis was the most common recurrence (n = 9), followed by other distant recurrences (n = 4) and local recurrences (n = 5). Median survival time for the group is 2.6 years, and median survival time (pathologic complete response) is 7.8 years. It is noteworthy that median survival time of patients with positive pretreatment lymph nodes (12 patients) was not reached. Surgical resection of Pancoast tumors after neoadjuvant high-dose radiation and chemotherapy can be safely performed. High-dose radiation in trimodality treatment is well tolerated and might be beneficial. Similar to other studies, late central nervous system relapse is problematic and indicates a need for assessing the role of prophylactic cranial irradiation in this disease.