Prognostic and predictive biomarkers in lung cancer. A review

Spatial colocalization and combined survival benefit of natural killer and CD8 T cells despite profound MHC class I loss in non-small cell lung cancer

BACKGROUND

Major histocompatibility complex class I (MHC-I) loss is frequent in non-small cell lung cancer (NSCLC) rendering tumor cells resistant to T cell lysis. NK cells kill MHC-I-deficient tumor cells, and although previous work indicated their presence at NSCLC margins, they were functionally impaired. Within, we evaluated whether NK cell and CD8 T cell infiltration and activation vary with MHC-I expression.

METHODS

We used single-stain immunohistochemistry (IHC) and Kaplan-Meier analysis to test the effect of NK cell and CD8 T cell infiltration on overall and disease-free survival. To delineate immune covariates of MHC-I-disparate lung cancers, we used multiplexed immunofluorescence (mIF) imaging followed by multivariate statistical modeling. To identify differences in infiltration and intercellular communication between IFNγ-activated and non-activated lymphocytes, we developed a computational pipeline to enumerate single-cell neighborhoods from mIF images followed by multivariate discriminant analysis.

RESULTS

Spatial quantitation of tumor cell MHC-I expression revealed intratumoral and intertumoral heterogeneity, which was associated with the local lymphocyte landscape. IHC analysis revealed that high CD56+ cell numbers in patient tumors were positively associated with disease-free survival (HR=0.58, p=0.064) and overall survival (OS) (HR=0.496, p=0.041). The OS association strengthened with high counts of both CD56+ and CD8+ cells (HR=0.199, p<1×10-3). mIF imaging and multivariate discriminant analysis revealed enrichment of both CD3+CD8+ T cells and CD3-CD56+ NK cells in MHC-I-bearing tumors (p<0.05). To infer associations of functional cell states and local cell-cell communication, we analyzed spatial single-cell neighborhood profiles to delineate the cellular environments of IFNγ+/- NK cells and T cells. We discovered that both IFNγ+ NK and CD8 T cells were more frequently associated with other IFNγ+ lymphocytes in comparison to IFNγ- NK cells and CD8 T cells (p<1×10-30). Moreover, IFNγ+ lymphocytes were most often found clustered near MHC-I+ tumor cells.

CONCLUSIONS

Tumor-infiltrating NK cells and CD8 T cells jointly affected control of NSCLC tumor progression. Coassociation of NK and CD8 T cells was most evident in MHC-I-bearing tumors, especially in the presence of IFNγ. Frequent colocalization of IFNγ+ NK cells with other IFNγ+ lymphocytes in near-neighbor analysis suggests NSCLC lymphocyte activation is coordinately regulated.

Lung Cancer: New Directions in Senior Patients Assessment

Age is but one significant prognostic factor in lung cancer, influencing survival, treatment response, and outcomes. This narrative review synthesizes findings from searches of 11 leading databases of research studies, systematic reviews, book chapters, and clinical trial reports on lung cancer in senior patients, with a focus on geriatric assessment as well as biomarkers. Key prognostic factors for lung cancer in seniors include biological age, functional capability, physical and psychological comorbidities, frailty, nutrition, status, and biomarkers like DNA methylation age. We identified the most valuable assessments that balance efficacy with quality of life. Optimizing care and improving outcomes with senior lung cancer patients benefits from a tailored therapeutic approach incorporating a complex geriatric assessment. A multidisciplinary collaboration between geriatricians, oncologists, and pulmonologists is crucial.

Spatial colocalization and combined survival benefit of natural killer and CD8 T cells despite profound MHC class I loss in non-small cell lung cancer

Background

MHC class I (MHC-I) loss is frequent in non-small cell lung cancer (NSCLC) rendering tumor cells resistant to T cell lysis. NK cells kill MHC-I-deficient tumor cells, and although previous work indicated their presence at NSCLC margins, they were functionally impaired. Within, we evaluated whether NK cell and CD8 T cell infiltration and activation vary with MHC-I expression.

Methods

We used single-stain immunohistochemistry (IHC) and Kaplan-Meier analysis to test the effect of NK cell and CD8 T cell infiltration on overall and disease-free survival. To delineate immune covariates of MHC-I-disparate lung cancers, we used multiplexed immunofluorescence (mIF) imaging followed by multivariate statistical modeling. To identify differences in infiltration and intercellular communication between IFNγ-activated and non-activated lymphocytes, we developed a computational pipeline to enumerate single cell neighborhoods from mIF images followed by multivariate discriminant analysis.

Results

Spatial quantitation of tumor cell MHC-I expression revealed intra- and inter-tumoral heterogeneity, which was associated with the local lymphocyte landscape. IHC analysis revealed that high CD56+ cell numbers in patient tumors were positively associated with disease-free survival (DFS) (HR=0.58, p=0.064) and overall survival (OS) (HR=0.496, p=0.041). The OS association strengthened with high counts of both CD56+ and CD8+ cells (HR=0.199, p<1×10-3). mIF imaging and multivariate discriminant analysis revealed enrichment of both CD3+CD8+ T cells and CD3-CD56+ NK cells in MHC-I-bearing tumors (p<0.05). To infer associations of functional cell states and local cell-cell communication, we analyzed spatial single cell neighborhood profiles to delineate the cellular environments of IFNγ+/- NK cells and T cells. We discovered that both IFNγ+ NK and CD8 T cells were more frequently associated with other IFNγ+ lymphocytes in comparison to IFNγ- NK cells and CD8 T cells (p<1×10-30). Moreover, IFNγ+ lymphocytes were most often found clustered near MHC-I+ tumor cells.

Conclusions

Tumor-infiltrating NK cells and CD8 T cells jointly affected control of NSCLC tumor progression. Co-association of NK and CD8 T cells was most evident in MHC-I-bearing tumors, especially in the presence of IFNγ. Frequent co-localization of IFNγ+ NK cells with other IFNγ+ lymphocytes in near-neighbor analysis suggests NSCLC lymphocyte activation is coordinately regulated.

Noncoding RNAs in cancer ferroptosis: From biology to clinical opportunity

Ferroptosis is a recently discovered pattern of programmed cell death that is nonapoptotic and irondependent. It is involved in lipid peroxidation dependent on reactive oxygen species. Ferroptosis has been verified to play a crucial regulatory role in a variety of pathological courses of disease, in particularly cancer. Emerging research has highlighted the potential of ferroptosis in tumorigenesis, cancer development and resistance to chemotherapy. However, the regulatory mechanism of ferroptosis remains unclear, which limits the application of ferroptosis in cancer treatment. Noncoding RNAs (ncRNAs) are noncoding transcripts that regulate gene expression in various ways to affect the malignant phenotypes of cancer cells. At present, the biological function and underlying regulatory mechanism of ncRNAs in cancer ferroptosis have been partially elucidated. Herein, we summarize the current knowledge of the central regulatory network of ferroptosis, with a focus on the regulatory functions of ncRNAs in cancer ferroptosis. The clinical application and prospects of ferroptosis-related ncRNAs in cancer diagnosis, prognosis and anticancer therapies are also discussed. Elucidating the function and mechanism of ncRNAs in ferroptosis, along with assessing the clinical significance of ferroptosis-related ncRNAs, provides new perspectives for understanding cancer biology and treatment approaches, which may benefit numerous cancer patients in the future.

Replication of Real-World Evidence in Oncology Using Electronic Health Record Data Extracted by Machine Learning

Meaningful real-world evidence (RWE) generation requires unstructured data found in electronic health records (EHRs) which are often missing from administrative claims; however, obtaining relevant data from unstructured EHR sources is resource-intensive. In response, researchers are using natural language processing (NLP) with machine learning (ML) techniques (i.e., ML extraction) to extract real-world data (RWD) at scale. This study assessed the quality and fitness-for-use of EHR-derived oncology data curated using NLP with ML as compared to the reference standard of expert abstraction. Using a sample of 186,313 patients with lung cancer from a nationwide EHR-derived de-identified database, we performed a series of replication analyses demonstrating some common analyses conducted in retrospective observational research with complex EHR-derived data to generate evidence. Eligible patients were selected into biomarker- and treatment-defined cohorts, first with expert-abstracted then with ML-extracted data. We utilized the biomarker- and treatment-defined cohorts to perform analyses related to biomarker-associated survival and treatment comparative effectiveness, respectively. Across all analyses, the results differed by less than 8% between the data curation methods, and similar conclusions were reached. These results highlight that high-performance ML-extracted variables trained on expert-abstracted data can achieve similar results as when using abstracted data, unlocking the ability to perform oncology research at scale.

Lung Cancer Subtype Diagnosis by Fusing Image-Genomics Data and Hybrid Deep Networks

Accurate diagnosis of cancer subtypes is crucial for precise treatment, because different cancer subtypes are involved with different pathology and require different therapies. Although deep learning techniques have made great success in computer vision and other fields, they do not work well on Lung cancer subtype diagnosis, due to the distinction of slide images between different cancer subtypes is ambiguous. Furthermore, they often over-fit to high-dimensional genomics data with limited samples, and do not fuse the image and genomics data in a sensible way. In this paper, we propose a hybrid deep network based approach LungDIG for Lung cancer subtype Diagnosis by fusing Image-Genomics data. LungDIG first tiles the tissue slide image into small patches and extracts the patch-level features by fine-tuning an Inception-V3 model. Since the patches may contain some false positives in non-diagnostic regions, it further designs a patch-level feature combination strategy to integrate the extracted patch features and maintain the diversity between different cancer subtypes. At the same time, it extracts the genomics features from Copy Number Variation data by an attention based nonlinear extractor. Next, it fuses the image and genomics features by an attention based multilayer perceptron (MLP) to diagnose cancer subtype. Experiments on TCGA lung cancer data show that LungDIG can not only achieve higher accuracy for cancer subtype diagnosis than state-of-the-art methods, but also have a high authenticity and good interpretability.

A Novel TP53 Gene Mutation Sustains Non-Small Cell Lung Cancer through Mitophagy

Lung cancer is the leading cause of cancer death in the world. In particular, non-small-cell lung cancer (NSCLC) represents the majority of the lung cancer population. Advances in DNA sequencing technologies have significantly contributed to revealing the roles, functions and mechanisms of gene mutations. However, the driver mutations that cause cancers and their pathologies remain to be explored. Here, we performed next-generation sequencing (NGS) on tumor tissues isolated from 314 Chinese NSCLC patients and established the mutational landscape in NSCLC. Among 656 mutations, we identified TP53-p.Glu358Val as a driver mutation in lung cancer and found that it activates mitophagy to sustain cancer cell growth. In support of this finding, mice subcutaneously implanted with NSCLC cells expressing TP53-p.Glu358Val developed larger tumors compared to wild-type cells. The pharmaceutical inhibition of autophagy/mitophagy selectively suppresses the cell proliferation of TP53-null or TP53-p.Glu358Val-expressing lung cancer cells. Together, our study characterizes a new TP53 mutation identified from Chinese lung cancer patients and uncovers its roles in regulating mitophagy, providing a new insight into NSCLC treatment.

Association between squamous cell carcinoma antigen level and EGFR mutation status in Chinese lung adenocarcinoma patients

Background

To investigate the association between squamous cell carcinoma antigen (SCCAg) level and epidermal growth factor receptor (EGFR) mutation status in Chinese lung adenocarcinoma patients.

Methods

We retrospectively analyzed 293 patients with lung adenocarcinoma, divided into EGFR mutant group (n = 178) and EGFR wild‐type group (n = 115). The general data and laboratory parameters of the two groups were compared. We used univariable and multivariable logistic regression to analyze the association between SCCAg level and EGFR mutation. Generalized additive model was used for curve fitting, and a hierarchical binary logistic regression model was used for interaction analysis.

Results

Squamous cell carcinoma antigen level in the EGFR wild‐type group was significantly higher than that in the mutant group (p < 0.001). After adjusting for confounding factors, we found that elevated SCCAg was associated with a lower probability of EGFR mutation, with an OR of 0.717 (95% CI: 0.543–0.947, p = 0.019). For the tripartite SCCAg groups, the increasing trend of SCCAg was significantly associated with the decreasing probability of EGFR mutation (p for trend = 0.015), especially for Tertile 3 versus Tertile 1 (OR = 0.505; 95% CI: 0.258–0.986; p = 0.045). Curve fitting showed that there was an approximate linear negative relationship between continuous SCCAg and EGFR mutation probability (p = 0.020), which was first flattened and then decreased (p < 0.001). The association between the two was consistent among different subgroups, suggesting no interaction (all p > 0.05).

Conclusion

There is a negative association between SCCAg level and EGFR mutation probability in Chinese lung adenocarcinoma patients.

Unraveling the Rewired Metabolism in Lung Cancer Using Quantitative NMR Metabolomics

Lung cancer cells are well documented to rewire their metabolism and energy production networks to enable proliferation and survival in a nutrient-poor and hypoxic environment. Although metabolite profiling of blood plasma and tissue is still emerging in omics approaches, several techniques have shown potential in cancer diagnosis. In this paper, the authors describe the alterations in the metabolic phenotype of lung cancer patients. In addition, we focus on the metabolic cooperation between tumor cells and healthy tissue. Furthermore, the authors discuss how metabolomics could improve the management of lung cancer patients.

Regulation of a Novel Splice Variant of Early Growth Response 4 (EGR4-S) by HER+ Signalling and HSF1 in Breast Cancer

The zinc finger transcription factor EGR4 has previously been identified as having a critical role in the proliferation of small cell lung cancer. Here, we have identified a novel, shortened splice variant of this transcription factor (EGR4-S) that is regulated by Heat Shock Factor-1 (HSF1). Our findings demonstrate that the shortened variant (EGR4-S) is upregulated with high EGFR, HER2, and H-Rasv12-expressing breast cell lines, and its expression is inhibited in response to HER pathway inhibitors. Protein and mRNA analyses of HER2+ human breast tumours indicated the novel EGR4-S splice variant to be preferentially expressed in tumour tissue and not detectable in patient-matched normal tissue. Knockdown of EGR4-S in the HER2-amplified breast cancer cell line SKBR3 reduced cell growth, suggesting that EGR4-S supports the growth of HER2+ tumour cells. In addition to chemical inhibitors of the HER2 pathway, EGR4-S expression was also found to be suppressed by chemical stressors and the overexpression of HSF1. Under these conditions, reduced EGR4-S levels were associated with the observed lower cell growth rate, but the augmentation of properties associated with higher metastatic potential. Taken together, these findings identify EGR4-S as a potential biomarker for HER2 pathway activation in human tumours that is regulated by HSF1.

The prognostic value of decrease in prognostic nutritional index in stage III non-small cell lung cancer patients during curative thoracic radiotherapy

BACKGROUND

Curative thoracic radiotherapy (CTRT) with concurrent chemotherapy has been considered as standard treatment approach for stage-III non-small cell lung cancer (NSCLC). The hematological and esophageal toxicities that have been encountered during CTRT would affect the immunonutritional status of the patients. The aim of this study is to evaluate the prognostic value of the change in pre- and post-treatment prognostic nutritional index (PNI) in stage-III NSCLC patients.

METHODS

Eighty seven consecutive stage III NSCLC patients' data were collected. Pre-radiotherapy (RT) and post-RT PNI values were calculated and the impact of prognostic value of PNI change on overall survival (OS) was evaluated by univariate and multivariate Cox regression analyses. A cutoff value of PNI change was obtained by receiver operator characteristic (ROC) curve analysis.

RESULTS

The cutoff value was found to be a 22% decrease in PNI by ROC curve analysis in terms of effect on OS. The median OS of low and high PNI decrease groups were 22.5 and 16.5 months respectively (P = 0,001). In univariate and multivariate analyses PNI decrease of ≥ 22% was found to be an independent poor prognostic factor for OS (P = 0.012) and hazard ratio (95% confidence interval)= 2.05 (1.16-3.62).

CONCLUSION

The PNI change would be a convenient parameter to assess the immunonutritional status of the patient at the end of CTRT. A decrease of more than 22% of PNI value may predict poor prognosis.

Management of Metastatic Nonsmall Cell Lung Cancer in Elderly

There is limited data on management of metastatic nonsmall cell lung cancer (NSCLC) in the elderly population due to lack of representation of this subset in clinical trials. The projected representation of elderly population of patients globally is expected to rise significantly in the years to come. It is imperative to understand the specific challenges and opportunities in management of elderly with NSCLC. Even in the elderly, the medical management of advanced NSCLC begins with driver mutation testing on lung biopsy. Once the patient is classified as driver mutation positive or negative, they can either be treated with a single-agent-targeted therapy or with immunotherapy and chemotherapy or after programmed death ligand 1 (PDL-1) assessment, with immunotherapy alone. After starting the appropriate therapy, the disease needs to be monitored at every 3 months with reassessment scans. Treatment in elderly should be designed as per their functional and not chronological age, and geriatric assessment scales should be utilized wherever possible to understand the functional age of the patient.

Electrospray Mediated Localized and Targeted Chemotherapy in a Mouse Model of Lung Cancer

Background: An advanced stage, centrally localized invasive tumor is a major cause of sudden death in lung cancer patients. Currently, chemotherapy, radiotherapy, laser ablation, or surgical resection if possible are the available state-of-the-art treatments but none of these guarantee remedy or long-term relief and are often associated with fatal complications. Allowing localized chemotherapy, by direct and confined drug delivery only at the tumor site, could be a promising option for preoperative down staging or palliative therapy. Here we report the localized and targeted application of intra tumor delivery of chemotherapeutics using a novel device based on the principle of electrospray.

Methods: C57BL/6J mice were injected with Lewis lung carcinoma cells subcutaneously. After 15 days, the animals were anesthetized and the tumors were exposed by skin incision. Tumors were electrosprayed with 100 µg cisplatin on days 0 and 2, and tumor volumes were measured daily. Animals were sacrificed on day 7 after the first electrospray and tumors were analyzed by immunohistochemistry.

Results: In this proof-of-concept study, we report that the tumor volume was reduced by 81.2% (22.46 ± 12.14 mm³) after two electrospray mediated Cisplatin deliveries, while the control tumor growth, at the same time point, increased by 200% (514.30 ± 104.50 mm³). Moreover, tunnel and Caspase-3 positive cells were increased after Cisplatin electrospray compared to other experimental groups of animals.

Conclusion: Targeted drug delivery by electrospray is efficient in the subcutaneous mouse model of lung cancer and offers a promising opportunity for further development toward its clinical application.

An application of machine learning based on real-world data: Mining features of fibrinogen in clinical stages of lung cancer between sexes

Background

Lung cancer is the most threatening malignant tumor to human health and life. Using a variety of machine learning algorithms and statistical analyses, this paper explores, discovers and demonstrates new indicators for the early diagnosis of lung cancer and their diagnostic performance from large samples of clinical data in the real world.

Methods

By applying machine learning methods, including minimum description length (MDL), naive Bayesian (NB), K-means (KM), nonnegative matrix factorization (NMF), and decision tree (DT), based on large sample data of 2,502 patients, we built a classification model and systematically explored differences in fibrinogen levels in different clinical stages of lung cancer between the sexes. We also validated the reliability of the model by testing it on a validation cohort of 447 patients. This report adheres to the “Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis” (TRIPOD) statement for the reporting of prediction models.

Results

The analysis revealed significant differences in fibrinogen levels, pleural effusion, chlorine levels, A-G ratio, glutamic-oxaloacetic transaminase and alkaline phosphatase levels as well as in sex composition between the early-stage lung cancer group and the middle-late-stage lung cancer group. The classification model created by the combination of fibrinogen, alkaline phosphatase and sex demonstrated good performance with an AUC of 73.5%. In addition, in males, a fibrinogen level of 2.94 g/L could initially serve as the upper limit for determining the early-stage lung cancer group, but a level of 3.91 g/L could be preliminarily used as a reference threshold for the lower limit for middle- to late-stage lung cancer. This latter level could also serve as the upper limit of the critical value for early-stage lung cancer in females.

Conclusions

An integrated application based on supervised and unsupervised machine learning algorithms could effectively explore the potential links contained in the clinical data and reveal the differences in fibrinogen levels in different clinical stages of lung cancer between the sexes, which could provide a new reference basis for lung cancer staging.

Next-generation sequencing demonstrates the rarity of short kinase variants specific to quadruple wild-type gastrointestinal stromal tumours

AIM

There is no known specific biomarker or genetic signal for quadruple wild-type (qWT) gastrointestinal stromal tumours (GISTs). By next-generation sequencing (NGS) of different GIST subgroups, this study aimed to characterise such a biomarker especially as a potential therapeutic target.

METHODS AND RESULTS

An NGS panel of 672 kinase genes was applied to DNA extracted from 11 wild-type GISTs (including three qWT GISTs) and 5 KIT/PDGFRA mutated GISTs. Short variants which were present in qWT GISTs but no other GIST subgroup were shortlisted. After removing common population variants, in silico-classified deleterious variants were found in CSNK2A1, MERTK, RHEB, ROCK1, PIKFYVE and TRRAP. None of these variants were demonstrated in a separate cohort of four qWT GISTs.

CONCLUSIONS

Short kinase variants which are specific to qWT GISTs are rare and are not universally demonstrated by this whole subgroup. It is therefore possible that the current definition of qWT GIST still covers a heterogenous population.

Biomarker testing for advanced lung cancer by next-generation sequencing; a valid method to achieve a comprehensive glimpse at mutational landscape

Background

Next-generation sequencing (NGS) based assay for finding an actionable driver in non-small-cell lung cancer is a less used modality in clinical practice. With a long list of actionable targets, limited tissue, arduous single-gene assays, the alternative of NGS for broad testing in one experiment looks attractive. We report here our experience with NGS for biomarker testing in hundred advanced lung cancer patients.

Methods

Predictive biomarker testing was performed using the Ion AmpliSeq™ Cancer Hotspot Panel V2 (30 tumors) and Oncomine™ Solid Tumor DNA and Oncomine™ Solid Tumor Fusion Transcript kit (70 tumors) on Ion-Torrent sequencing platform.

Results

One-seventeen distinct aberrations were detected across 29 genes in eighty-six tumors. The most commonly mutated genes were TP53 (43% cases), EGFR (23% cases) and KRAS (17% cases). Thirty-four patients presented an actionable genetic variant for which targeted therapy is presently available, and fifty-two cases harbored non-actionable variants with the possibility of recruitment in clinical trials. NGS results were validated by individual tests for detecting EGFR mutation, ALK1 rearrangement, ROS1 fusion, and c-MET amplification. Compared to single test, NGS exhibited good agreement for detecting EGFR mutations and ALK1 fusion (sensitivity- 88.89%, specificity- 100%, Kappa-score 0.92 and sensitivity- 80%, specificity- 100%, Kappa-score 0.88; respectively). Further, the response of patients harboring tyrosine kinase inhibitor (TKI) sensitizing EGFR mutations was assessed. The progression-free-survival of EGFR positive patients on TKI therapy, harboring a concomitant mutation in PIK3CA-mTOR and/or RAS-RAF-MAPK pathway gene and/or TP53 gene was inferior to those with sole-sensitizing EGFR mutation (2 months vs. 9.5 months, P = 0.015).

Conclusions

This is the first study from South Asia looking into the analytical validity of NGS and describing the mutational landscape of lung cancer patients to study the impact of co-mutations on cancer biology and treatment outcome. Our study demonstrates the clinical utility of NGS testing for identifying actionable variants and making treatment decisions in advanced lung cancer.

Identification of a Sixteen-gene Prognostic Biomarker for Lung Adenocarcinoma Using a Machine Learning Method

Objectives: Lung adenocarcinoma (LUAD) accounts for a majority of cancer-related deaths worldwide annually. The identification of prognostic biomarkers and prediction of prognosis for LUAD patients is necessary. Materials and Methods: In this study, LUAD RNA-Seq data and clinical data from the Cancer Genome Atlas (TCGA) were divided into TCGA cohort I (n = 338) and II (n = 168). The cohort I was used for model construction, and the cohort II and data from Gene Expression Omnibus (GSE72094 cohort, n = 393; GSE11969 cohort, n = 149) were utilized for validation. First, the survival-related seed genes were selected from the cohort I using the machine learning model (random survival forest, RSF), and then in order to improve prediction accuracy, the forward selection model was utilized to identify the prognosis-related key genes among the seed genes using the clinically-integrated RNA-Seq data. Second, the survival risk score system was constructed by using these key genes in the cohort II, the GSE72094 cohort and the GSE11969 cohort, and the evaluation metrics such as HR, p value and C-index were calculated to validate the proposed method. Third, the developed approach was compared with the previous five prediction models. Finally, bioinformatics analyses (pathway, heatmap, protein-gene interaction network) have been applied to the identified seed genes and key genes. Results and Conclusion: Based on the RSF model and clinically-integrated RNA-Seq data, we identified sixteen key genes that formed the prognostic gene expression signature. These sixteen key genes could achieve a strong power for prognostic prediction of LUAD patients in cohort II (HR = 3.80, p = 1.63e-06, C-index = 0.656), and were further validated in the GSE72094 cohort (HR = 4.12, p = 1.34e-10, C-index = 0.672) and GSE11969 cohort (HR = 3.87, p = 6.81e-07, C-index = 0.670). The experimental results of three independent validation cohorts showed that compared with the traditional Cox model and the use of standalone RNA-Seq data, the machine-learning-based method effectively improved the prediction accuracy of LUAD prognosis, and the derived model was also superior to the other five existing prediction models. KEGG pathway analysis found eleven of the sixteen genes were associated with Nicotine addiction. Thirteen of the sixteen genes were reported for the first time as the LUAD prognosis-related key genes. In conclusion, we developed a sixteen-gene prognostic marker for LUAD, which may provide a powerful prognostic tool for precision oncology.

Impact of Heat Shock Protein 90 Inhibition on the Proteomic Profile of Lung Adenocarcinoma as Measured by Two-Dimensional Electrophoresis Coupled with Mass Spectrometry

Heat shock protein 90 (HSP90) is an important chaperone in lung adenocarcinoma, with relevant protein drivers such as EGFR (epidermal growth factor receptor) and EML4-ALK (echinoderm microtubule-associated protein-like protein4 fused to anaplastic lymphoma kinase) depending on it for their correct function, therefore HSP90 inhibitors show promise as potential treatments for lung adenocarcinoma. To study responses to its inhibition, HSP90 was pharmacologically interrupted by geldanamycin and resorcinol derivatives or with combined inhibition of HSP90 plus HSP70 in lung adenocarcinoma cell lines. Two-dimensional electrophoresis was performed to identify proteomic profiles associated with inhibition which will help to understand the biological basis for the responses. HSP90 inhibition resulted in altered protein profiles that differed according the treatment condition studied. Results revealed 254 differentially expressed proteins after treatments, among which, eukaryotic translation initiation factor3 subunit I (eIF3i) and citrate synthase demonstrated their potential role as response biomarkers. The differentially expressed proteins also enabled signalling pathways involved in responses to be identified; these included apoptosis, serine-glycine biosynthesis and tricarboxylic acid cycle. The proteomic profiles identified here contribute to an improved understanding of HSP90 inhibition and open possibilities for the detection of potential response biomarkers which will be essential to maximize treatment efficacy in lung adenocarcinoma.

A Simulation Study Comparing Different Statistical Approaches for the Identification of Predictive Biomarkers

Identification of relevant biomarkers that are associated with a treatment effect is one requirement for adequate treatment stratification and consequently to improve health care by administering the best available treatment to an individual patient. Various statistical approaches were proposed that allow assessing the interaction between a continuous covariate and treatment. Nevertheless, categorization of a continuous covariate, e.g., by splitting the data at the observed median value, appears to be very prevalent in practice. In this article, we present a simulation study considering data as observed in a randomized clinical trial with a time-to-event outcome performed to compare properties of such approaches, namely, Cox regression with linear interaction, Multivariable Fractional Polynomials for Interaction (MFPI), Local Partial-Likelihood Bootstrap (LPLB), and the Subpopulation Treatment Effect Pattern Plot (STEPP) method, and of strategies based on categorization of continuous covariates (splitting the covariate at the median, splitting at quartiles, and using an "optimal" split by maximizing a corresponding test statistic). In different scenarios with no interactions, linear interactions or nonlinear interactions, type I error probability and the power for detection of a true covariate-treatment interaction were estimated. The Cox regression approach was more efficient than the other methods for scenarios with monotonous interactions, especially when the number of observed events was small to moderate. When patterns of the biomarker-treatment interaction effect were more complex, MFPI and LPLB performed well compared to the other approaches. Categorization of data generally led to a loss of power, but for very complex patterns, splitting the data into multiple categories might help to explore the nature of the interaction effect. Consequently, we recommend application of statistical methods developed for assessment of interactions between continuous biomarkers and treatment instead of arbitrary or data-driven categorization of continuous covariates.

Microfluidic-Based Immunohistochemistry Combined With Next-Generation Sequencing on Diagnostic Tissue Sections for Detection of Tumoral BRAF V600E Mutation

OBJECTIVES

Tailored diagnostics requires immunohistochemistry (IHC) and next generation sequencing (NGS). Here we combined on a single paraffin-embedded slide microfluidic-based IHC (micro-IHC) and NGS for BRAF V600E mutation detection in BRAFomas.

METHODS

For micro-IHC, we performed the primary antibody incubation step of conventional chromogenic IHC in a LabSat device (Lunaphore Technologies SA). Tumor areas immunoreactive for pan-cytokeratin, pan-melanoma, and BRAF V600E mutation-specific antibody were H-scored, microdissected, and analyzed by NGS.

RESULTS

After 2 minutes, pan-cytokeratin and BRAF micro-IHC increased exponentially (half-time values: 1.7 and 3.2 minutes). Pan-melanoma displayed a higher half-time value of 15 minutes. There was no significant difference in H-score and staining quality, respectively, between conventional and micro-IHC. BRAF V600E mutation was detected in all pan-cytokeratin and pan-melanoma stained samples without amplification but in only 40% of BRAF V600E stained samples with amplification.

CONCLUSIONS

Micro-IHC enables short antibody incubation times and subsequent NGS. Preprocessing is critical for preservation of DNA quality.

Blood serum proteins as biomarkers for prediction of survival, locoregional control and distant metastasis rate in radiotherapy and radio-chemotherapy for non-small cell lung cancer

BACKGROUND

Several studies have documented that blood biomarkers can improve basic prognostic models in radiotherapy and radio-chemotherapy for non-small cell lung cancer. The current study evaluated the prognostic impact of six markers focusing on their utility in homogenous subsets, compared to the significance in a large heterogeneous group.

METHODS

Blood samples of 337 patients who were referred for curative or palliative external beam thoracic radiotherapy for non-small cell lung cancer were collected. The concentration of osteopontin (OPN), vascular endothelial growth factor (VEGF), erythropoetin (EPO), high mobility group box 1 protein (HMGB1), insulin-like growth factor 1 (IGF-1) and platelet-derived growth factor (PDGF) in serum were measured by ELISA assay and the prognostic potential was assessed using univariable and multivariable survival models.

RESULTS

Multivariable analysis revealed that out of several variables studied six dichotomized features: namely: cigarette smoking, lack of chemotherapy, palliative doses of radiotherapy, high OPN concentration, advanced T stage and high VEGF concentration had a highly significant (p < 0.005) and independent influence on overall survival in the group of 337 patients. In a subset of patients treated with curative radio-chemotherapy or radiotherapy (N = 148) tumor pathology, EPO concentration and VEGF concentration, significantly and independently influenced overall survival. In a subset of patients with squamous cell cancer (N = 206) OPN had a highly significant impact on overall survival. In contrast, in a subset of patients with nonsquamous histology (N = 131) only VEGF had a significant influence on survival.

CONCLUSIONS

Blood serum proteins appear to be clinically useful prognosticators of overall survival in radio-chemotherapy and radiotherapy for non-small cell lung cancer. In unselected heterogeneous groups, dichotomized concentrations of OPN and VEGF emerged among the strongest independent prognosticators of overall survival. VEGF and EPO concentration (dichotomized) were found to be independent prognostic factors among the patients treated with curative doses of radiotherapy. The utility of OPN as a prognostic marker appeared restricted to the patients with squamous histology.

Prophylactic Dermatologic Treatment of Afatinib-Induced Skin Toxicities in Patients with Metastatic Lung Cancer: A Pilot Study

BACKGROUND

Severe skin rash is listed among important side effects of EGFR tyrosine kinase inhibitors. Polydatin (PD), a glycosylated polyphenol, is endowed with anti-inflammatory activity in human epidermal keratinocytes.

OBJECTIVE

This study evaluated the effect of topical application of a moisturizer containing PD to prevent skin rash in patients with mutated non-small cell lung cancer (NSCLC) treated with afatinib.

MATERIALS AND METHODS

Eligible NSCLC patients with metastatic disease were treated with first-line afatinib 40 mg/die. One day before starting systemic therapy, all patients received topical administration of a 1.5% PD-based cream b.i.d. every day until the end of afatinib treatment.

RESULTS

Out of 34 treated patients, the incidence of skin rash (all grades) was 41.2% and grade 2 rash was 20.6%, and grade 3 rash was not observed in any of the patients. None of the patients discontinued therapy for toxicity. The mean duration of treatment was 6.4 months, calculated from the time treatment was started to the date treatment was stopped.

CONCLUSION

The results showed that a PD-based cream can reduce the incidence of grade ≥2 skin toxicities in patients treated with afatinib. Clinical study registration number: Prot. No. 130/CE Lazio 1 Italy.

Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning

Visual inspection of histopathology slides is one of the main methods used by pathologists to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent subtypes of lung cancer, and their distinction requires visual inspection by an experienced pathologist. In this study, we trained a deep convolutional neural network (inception v3) on whole-slide images obtained from The Cancer Genome Atlas to accurately and automatically classify them into LUAD, LUSC or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues and biopsies. Furthermore, we trained the network to predict the ten most commonly mutated genes in LUAD. We found that six of them-STK11, EGFR, FAT1, SETBP1, KRAS and TP53-can be predicted from pathology images, with AUCs from 0.733 to 0.856 as measured on a held-out population. These findings suggest that deep-learning models can assist pathologists in the detection of cancer subtype or gene mutations. Our approach can be applied to any cancer type, and the code is available at https://github.com/ncoudray/DeepPATH .

A Fluorescence Quenching Assay Based on Molecular Beacon Formation through a Ligase Detection Reaction for Facile and Rapid Detection of Point Mutations

A fluorescence quenching assay based on a ligase detection reaction was developed for facile and rapid detection of point mutations present in a mixed population of non-variant DNA. If the test DNA carried a targeted mutation, then the two allele-specific primers were ligated to form a molecular beacon resulting in the expected fluorescence quenching signatures. Using this method, we successfully detected as low as 5% mutant DNA in a mixture of wild-type DNA (t test at 99% confidence level).

An Update on Predictive Biomarkers for Treatment Selection in Non-Small Cell Lung Cancer

It is now widely established that management of lung cancer is much more complex and cannot be centered on the binary classification of small-cell versus non-small cell lung cancer (NSCLC). Lung cancer is now recognized as a highly heterogeneous disease that develops from genetic mutations and gene expression patterns, which initiate uncontrolled cellular growth, proliferation and progression, as well as immune evasion. Accurate biomarker assessment to determine the mutational status of driver mutations such as EGFR, ALK and ROS1, which can be targeted by specific tyrosine kinase inhibitors, is now essential for treatment decision making in advanced stage NSCLC and has shifted the treatment paradigm of NSCLC to more individualized therapy. Rapid advancements in immunotherapeutic approaches to NSCLC treatment have been paralleled by development of a range of potential predictive biomarkers that can enrich for patient response, including PD-L1 expression and tumor mutational burden. Here, we review the key biomarkers that help predict response to treatment options in NSCLC patients.

A stitch in time saves nine: external quality assessment rounds demonstrate improved quality of biomarker analysis in lung cancer

Biomarker analysis has become routine practice in the treatment of non-small cell lung cancer (NSCLC). To ensure high quality testing, participation to external quality assessment (EQA) schemes is essential. This article provides a longitudinal overview of the EQA performance for EGFR, ALK, and ROS1 analyses in NSCLC between 2012 and 2015.

The four scheme years were organized by the European Society of Pathology according to the ISO 17043 standard. Participants were asked to analyze the provided tissue using their routine procedures.

Analysis scores improved for individual laboratories upon participation to more EQA schemes, except for ROS1 immunohistochemistry (IHC). For EGFR analysis, scheme error rates were 18.8%, 14.1% and 7.5% in 2013, 2014 and 2015 respectively. For ALK testing, error rates decreased between 2012 and 2015 by 5.2%, 3.2% and 11.8% for the fluorescence in situ hybridization (FISH), FISH digital, and IHC subschemes, respectively. In contrast, for ROS1 error rates increased between 2014 and 2015 for FISH and IHC by 3.2% and 9.3%. Technical failures decreased over the years for all three markers.

Results show that EQA contributes to an ameliorated performance for most predictive biomarkers in NSCLC. Room for improvement is still present, especially for ROS1 analysis.

Classification and Pathology of Lung Cancer

Advancement in the understanding of lung tumor biology enables continued refinement of lung cancer classification, reflected in the recently introduced 2015 World Health Organization classification of lung cancer. In small biopsy or cytology specimens, special emphasis is placed on separating adenocarcinomas from the other lung cancers to effectively select tumors for targeted molecular testing. In resection specimens, adenocarcinomas are further classified based on architectural pattern to delineate tissue types of prognostic significance. Neuroendocrine tumors are divided into typical carcinoid, atypical carcinoid, small cell carcinoma, and large cell neuroendocrine carcinoma based on a combination of features, especially tumor cell proliferation rate.

Update on Immunohistochemistry for the Diagnosis of Lung Cancer

Immunohistochemistry is a widely available technique that is less challenging and can provide clinically meaningful results quickly and cost-efficiently in comparison with other techniques. In addition, immunohistochemistry allows for the evaluation of cellular localization of proteins in the context of tumor structure. In an era of precision medicine, pathologists are required to classify lung cancer into specific subtypes and assess biomarkers relevant to molecular-targeted therapies. This review summarizes the hot topics of immunohistochemistry in lung cancer, including (i) adenocarcinoma vs squamous cell carcinoma; (ii) neuroendocrine markers; (iii) ALK, ROS1, and EGFR; (iv) PD-L1 (CD274); (v) lung carcinoma vs malignant mesothelioma; and (vi) NUT carcinoma. Major pitfalls in evaluating immunohistochemical results are also described.

Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment With Targeted Tyrosine Kinase Inhibitors: Guideline From the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology

CONTEXT

- In 2013, an evidence-based guideline was published by the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology to set standards for the molecular analysis of lung cancers to guide treatment decisions with targeted inhibitors. New evidence has prompted an evaluation of additional laboratory technologies, targetable genes, patient populations, and tumor types for testing.

OBJECTIVE

- To systematically review and update the 2013 guideline to affirm its validity; to assess the evidence of new genetic discoveries, technologies, and therapies; and to issue an evidence-based update.

DESIGN

- The College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology convened an expert panel to develop an evidence-based guideline to help define the key questions and literature search terms, review abstracts and full articles, and draft recommendations.

RESULTS

- Eighteen new recommendations were drafted. The panel also updated 3 recommendations from the 2013 guideline.

CONCLUSIONS

- The 2013 guideline was largely reaffirmed with updated recommendations to allow testing of cytology samples, require improved assay sensitivity, and recommend against the use of immunohistochemistry for EGFR testing. Key new recommendations include ROS1 testing for all adenocarcinoma patients; the inclusion of additional genes ( ERBB2, MET, BRAF, KRAS, and RET) for laboratories that perform next-generation sequencing panels; immunohistochemistry as an alternative to fluorescence in situ hybridization for ALK and/or ROS1 testing; use of 5% sensitivity assays for EGFR T790M mutations in patients with secondary resistance to EGFR inhibitors; and the use of cell-free DNA to "rule in" targetable mutations when tissue is limited or hard to obtain.

Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment With Targeted Tyrosine Kinase Inhibitors: Guideline From the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology

CONTEXT

In 2013, an evidence-based guideline was published by the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology to set standards for the molecular analysis of lung cancers to guide treatment decisions with targeted inhibitors. New evidence has prompted an evaluation of additional laboratory technologies, targetable genes, patient populations, and tumor types for testing.

OBJECTIVE

To systematically review and update the 2013 guideline to affirm its validity; to assess the evidence of new genetic discoveries, technologies, and therapies; and to issue an evidence-based update.

DESIGN

The College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology convened an expert panel to develop an evidence-based guideline to help define the key questions and literature search terms, review abstracts and full articles, and draft recommendations.

RESULTS

Eighteen new recommendations were drafted. The panel also updated 3 recommendations from the 2013 guideline.

CONCLUSIONS

The 2013 guideline was largely reaffirmed with updated recommendations to allow testing of cytology samples, require improved assay sensitivity, and recommend against the use of immunohistochemistry for EGFR testing. Key new recommendations include ROS1 testing for all adenocarcinoma patients; the inclusion of additional genes (ERBB2, MET, BRAF, KRAS, and RET) for laboratories that perform next-generation sequencing panels; immunohistochemistry as an alternative to fluorescence in situ hybridization for ALK and/or ROS1 testing; use of 5% sensitivity assays for EGFR T790M mutations in patients with secondary resistance to EGFR inhibitors; and the use of cell-free DNA to "rule in" targetable mutations when tissue is limited or hard to obtain.

Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment With Targeted Tyrosine Kinase Inhibitors: Guideline From the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology

CONTEXT

In 2013, an evidence-based guideline was published by the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology to set standards for the molecular analysis of lung cancers to guide treatment decisions with targeted inhibitors. New evidence has prompted an evaluation of additional laboratory technologies, targetable genes, patient populations, and tumor types for testing.

OBJECTIVE

To systematically review and update the 2013 guideline to affirm its validity; to assess the evidence of new genetic discoveries, technologies, and therapies; and to issue an evidence-based update.

DESIGN

The College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology convened an expert panel to develop an evidence-based guideline to help define the key questions and literature search terms, review abstracts and full articles, and draft recommendations.

RESULTS

Eighteen new recommendations were drafted. The panel also updated 3 recommendations from the 2013 guideline.

CONCLUSIONS

The 2013 guideline was largely reaffirmed with updated recommendations to allow testing of cytology samples, require improved assay sensitivity, and recommend against the use of immunohistochemistry for EGFR testing. Key new recommendations include ROS1 testing for all adenocarcinoma patients; the inclusion of additional genes (ERBB2, MET, BRAF, KRAS, and RET) for laboratories that perform next-generation sequencing panels; immunohistochemistry as an alternative to fluorescence in situ hybridization for ALK and/or ROS1 testing; use of 5% sensitivity assays for EGFR T790M mutations in patients with secondary resistance to EGFR inhibitors; and the use of cell-free DNA to "rule in" targetable mutations when tissue is limited or hard to obtain.

Blockade efficacy of MEK/ERK-dependent autophagy enhances PI3K/Akt inhibitor NVP-BKM120's therapeutic effectiveness in lung cancer cells

NVP-BKM120 (BKM120) is a new pan-class I phosphatidylinositol-3 kinase (PI3K) inhibitor and has been tested in clinical trials as an anticancer agent. In this study, we determined whether BKM120 induces autophagy and the impact of autophagy induction on BKM120's growth-inhibitory activity. BKM120 potently induced elevation of autophagosome-bound type II LC3 (LC3-II) protein, predominantly in cell lines insensitive to BKM120, thereby inducing autophagy. The presence of lysosomal protease inhibitor chloroquine further enhanced the levels of LC3-II. BKM120 combined with chloroquine, enhanced growth-inhibitory effects including induction of apoptosis, suggesting that autophagy is a protective mechanism counteracting BKM120's growth-inhibitory activity. Interestingly, BKM120 increased p-ERK1/2 levels. When blocking the activation of this signaling with MEK inhibitors or with knockdown of ERK1/2, the ability of BKM120 to increase LC3-II was attenuated and the growth-inhibitory effects including induction of apoptosis were accordingly enhanced, suggesting that the MEK/ERK activation contributes to BKM120-induced authophagy. In mouse xenograft model, we also found that the combination of BKM120 and PD0325901 synergistically suppressed cell growth in human lung cancer cells. Thus, the current study not only reveals mechanisms accounting for BKM120-induced autophagy, but also suggests an alternative method to enhance BKM120's therapeutic efficacy against non-small cell lung cancer(NSCLC) by blocking autophagy with either a lysosomal protease inhibitor or MEK inhibitor.

Nonsmall cell lung carcinoma: diagnostic difficulties in small biopsies and cytological specimens

The pathological and molecular classification of lung cancer has become substantially more complex over the past decade. For diagnostic purposes on small samples, additional stains are frequently required to distinguish between squamous cell carcinoma and adenocarcinoma. Subsequently, for advanced nonsquamous cell nonsmall cell lung carcinoma (NSCLC) patients, predictive analyses on epidermal growth factor receptor, anaplastic lymphoma kinase and ROS1 are required. In NSCLCs negative for these biomarkers, programmed death ligand-1 immunohistochemistry is performed. Small samples (biopsy and cytology) require “tissue” management, which is best achieved by the interaction of all physicians involved.

CircRNA: functions and properties of a novel potential biomarker for cancer

Circular RNAs, a novel class of endogenous noncoding RNAs, are characterized by their covalently closed loop structures without a 5′ cap or a 3′ Poly A tail. Although the mechanisms of circular RNAs’ generation and function are not fully clear, recent research has shown that circular RNAs may function as potential molecular markers for disease diagnosis and treatment and play an important role in the initiation and progression of human diseases, especially in tumours. This review summarizes some information about categories, biogenesis, functions at the molecular level, properties of circular RNAs and the possibility of circular RNAs as biomarkers in cancers.

Advances in Circulating Tumor DNA Analysis

The analysis of cell-free circulating tumor DNA (ctDNA) is a very promising tool and might revolutionize cancer care with respect to early detection, identification of minimal residual disease, assessment of treatment response, and monitoring tumor evolution. ctDNA analysis, often referred to as "liquid biopsy" offers what tissue biopsies cannot-a continuous monitoring of tumor-specific changes during the entire course of the disease. Owing to technological improvements, efforts for the establishment of preanalytical and analytical benchmark, and the inclusion of ctDNA analyses in clinical trial, an actual clinical implementation has come within easy reach. In this chapter, recent advances of the analysis of ctDNA are summarized starting from the discovery of cell-free DNA, to methodological approaches and the clinical applicability.

Testing for ROS1 in non-small cell lung cancer: a review with recommendations

Rearrangements of the ROS1 gene occur in 1-2 % of non-small cell lung cancers (NSCLCs). Crizotinib, a highly effective inhibitor of ROS1 kinase activity, is now FDA-approved for the treatment of patients with advanced ROS1-positive NSCLC. Consequently, focus on ROS1 testing is growing. Most laboratories currently rely on fluorescence in situ hybridisation (FISH) assays using a dual-colour break-apart probe to detect ROS1 rearrangements. Given the rarity of these rearrangements in NSCLC, detection of elevated ROS1 protein levels by immunohistochemistry may provide cost-effective screening prior to confirmatory FISH testing. Non-in situ testing approaches also hold potential as stand-alone methods or complementary tests, including multiplex real-time PCR assays and next-generation sequencing (NGS) platforms which include commercial test kits covering a range of fusion genes. In order to ensure high-quality biomarker testing, appropriate tissue handling, adequate control materials and participation in external quality assessment programmes are essential, irrespective of the testing technique employed. ROS1 testing is often only considered after negative tests for EGFR mutation and ALK gene rearrangement, based on the assumption that these oncogenic driver events tend to be exclusive. However, as the use of ROS1 inhibitors becomes routine, accurate and timely detection of ROS1 gene rearrangements will be critical for the optimal treatment of patients with NSCLC. As NGS techniques are introduced into routine diagnostic practice, ROS1 fusion gene testing will be provided as part of the initial testing package.

Correlation between EGFR Gene Mutations and Lung Cancer: a Hospital-Based Study

Epidermal growth factor receptor (EGFR) is one of the targeted molecular markers in many cancers including lung malignancies. Gefitinib and erlotinib are two available therapeutics that act as specific inhibitors of tyrosine kinase (TK) domains. We performed a case-control study with formalin-fixed paraffin-embedded tissue blocks (FFPE) from tissue biopsies of 167 non-small cell lung carcinoma (NSCLC) patients and 167 healthy controls. The tissue biopsies were studied for mutations in exons 18-21 of the EGFR gene. This study was performed using PCR followed by DNA sequencing. We identified 63 mutations in 33 men and 30 women. Mutations were detected in exon 19 (delE746-A750, delE746-T751, delL747-E749, delL747-P753, delL747-T751) in 32 patients, exon 20 (S786I, T790M) in 16, and exon 21 (L858R) in 15. No mutations were observed in exon 18. The 63 patients with EFGR mutations were considered for upfront therapy with oral tyrosine kinase inhibitor (TKI) drugs and have responded well to therapy over the last 15 months. The control patients had no mutations in any of the exons studied. The advent of EGFR TKI therapy has provided a powerful new treatment modality for patients diagnosed with NSCLC. The study emphasizes the frequency of EGFR mutations in NSCLC patients and its role as an important predictive marker for response to oral TKI in the south Indian population.

Neueste technologische Entwicklungen für die Analyse von zirkulierender Tumor-DNA

Die Analyse von zirkulierender Tumor-DNA, zusammen mit der Analyse von zirkulierenden Tumorzellen auch oft Liquid Biopsy genannt, ist ein sich rasch entwickelndes Feld in der medizinischen Forschung. Obwohl es von der Entdeckung der zellfreien DNA bis hin zur Erkenntnis, dass sie sich als Biomarker eignet, Jahrzehnte gedauert hat, wurde der klinische Nutzen der ctDNA hinsichtlich der Überwachung des Therapieansprechens, der Identifizierung von Resistenzmechanismen und neu aufkommenden Therapiezielen sowie der Detektion von minimaler Resterkrankung mittlerweile in unzähligen Studien bewiesen.

Aufgrund der hohen Variabilität, mit der ctDNA in der Zirkulation vorkommt, sowie der starken Fragmentierung, stellt die ctDNA aber einen schwierigen Analyten dar. In den letzten Jahren haben erhebliche technologische Fortschritte dazu beigetragen, dass eine Routineanwendung der ctDNA-Analysen tatsächlich realisierbar wird, sofern eine Reihe von regulatorischen Hürden überwunden wird.

Serum anti-MDM2 and anti-c-Myc autoantibodies as biomarkers in the early detection of lung cancer

This study aims to investigate the clinical significance of serum autoantibodies against MDM2 and c-Myc and evaluate their feasibility in the immunodiagnosis of lung cancer. 50 sera samples with 43 available paired lung cancer tissue and adjacent normal tissue slides with follow up information and 44 sera from normal human controls (NHC) were used in the research group. Another 62 lung cancer sera and 43 NHC sera were used in the validation group. The results of IHC showed that MDM2 and c-Myc protein were overexpressed in lung cancer tissues compared to adjacent normal tissues (p < 0.001). Likewise, significantly higher levels of serum autoantibodies against MDM2 and c-Myc were found in lung cancer compared to NHC both in research and validation groups. Further analysis on IHC and ELISA results showed that serum level of autoantibodies against these two TAAs were positively associated with tissue staining scores (both p < 0.05). The area under curve (AUC) values of anti-MDM2 and anti-cMyc autoantibodies for discriminating lung cancers from NHC were 0.698 and 0.636 in research group, 0.777 and 0.815 in the validation group, respectively. Both anti-MDM2 and anti-c-Myc autoantibodies can discriminate stage I lung cancer patients from NHC with AUC values of 0.703 and 0.662. Kaplan-Meier analysis showed that higher level of serum anti-c-Myc autoantibodies was significantly related to shortened disease-free survival (DFS) (p = 0.041). In conclusion, our finding suggested that serum MDM2 and c-Myc autoantibodies may have the potential to serve as non-invasive diagnostic biomarkers in patients with lung cancer.

Correlation between EGFR gene mutation, cytologic tumor markers, 18F-FDG uptake in non-small cell lung cancer

Background

EGFR mutation-induced cell proliferation causes changes in tumor biology and tumor metabolism, which may reflect tumor marker concentration and 18F-FDG uptake on PET/CT. Direct aspirates of primary lung tumors contain different concentrations of tumor markers than serum tumor markers, and may correlate better with EGFR mutation than serum tumor markers.

The purpose of this study is to investigate an association between cytologic tumor markers and FDG uptake with EGFR mutation status in non-small cell lung cancer (NSCLC).

Methods

We prospectively collected tumor aspirates of 61 patients who underwent EGFR mutation analysis. Serum and cytologic CYFRA 21-1, CEA, and SCCA levels were measured and correlated with EGFR gene mutations. FDG PET/CT was performed on 58 patients for NSCLC staging, and SUV was correlated with EGFR mutation status.

Results

Thirty (50 %) patients had EGFR mutation and 57 patients had adenocarcinoma subtype. Univariate analysis showed that female gender, never smoker, high levels of cytologic CYFRA 21-1 (c-CYFRA) and lower maximum standard uptake value (SUVmax) were correlated with EGFR mutations. ROC generated cut-off values of 20.8 ng/ml for c-CYFRA and SUVmax of 9.6 showed highest sensitivity for EGFR mutation detection. Multivariate analysis revealed that female gender [hazard ratio (HR): 18.15, p = 0.025], higher levels of c-CYFRA (HR: 7.58, and lower SUVmax (HR: 0.08, p = 0.005) were predictive of harboring EGFR mutation.

Conclusions

The cytologic tumor marker c-CYFRA was positively associated with EGFR mutations in NSCLC. EGFR mutation-positive NSCLCs have relatively lower glycolysis compared with NSCLCs without EGFR mutation.

Potential crosstalk between cofilin-1 and EGFR pathways in cisplatin resistance of non-small-cell lung cancer

Current challenge in oncology is to establish the concept of personalized medicine in clinical practice. In this context, non-small-cell lung cancer (NSCLC) presents clinical, histological and molecular heterogeneity, being one of the most genomically diverse of all cancers. Recent advances added Epidermal Growth Factor Receptor (EGFR) as a predictive biomarker for patients with advanced NSCLC. In tumors with activating EGFR mutations, tyrosine kinase inhibitors (TKI) are indicated as first-line treatment, although restricted to a very small target population. In this context, cofilin-1 (a cytosolic protein involved with actin dynamics) has been widely studied as a biomarker of an aggressive phenotype in tumors, and overexpression of cofilin-1 is associated with cisplatin resistance and poor prognosis in NSCLC. Here, we gather information about the predictive potential of cofilin-1 and reviewed the crosstalk between cofilin-1/EGFR pathways. We aimed to highlight new perspectives of how these interactions might affect cisplatin resistance in NSCLC. We propose that cofilin-1 quantification in clinical samples in combination with presence/absence of EGFR mutation could be used to select patients that would benefit from TKI's treatment. This information is of paramount importance and could result in a possibility of guiding more effective treatments to NSCLC patients.