Different pulmonary adenocarcinoma growth patterns significantly affect survival

Heldwein, M.; Schlachtenberger, Georg; Doerr, Fabian; Menghesha, Hruy; Bennink, Gerardus; Schröder, Karl-Moritz; Schäfer, Stephan; Wahlers, Thorsten; Hekmat, Khosro

doi:10.1016/j.suronc.2021.101674

Cited by 2 publications

(2 citation statements)

References 32 publications

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“…It is worth noting that carcinomas are a heterogeneous group of malignant neoplasms of epithelial cell origin ( 32 ), which can be classified according to their histologic subtype (squamous cell carcinoma vs. adenocarcinoma) ( 33 ) or according to tissue of origin (e.g., lung or breast carcinomas) ( 34 ). Even when arising from the same organ, carcinomas may have a wide variety of growth and differentiation patterns, depending also on their histological subtypes; as an example, basal cell carcinoma variants can have a nodular, superficial, micronodular, infiltrative, or metatypical pattern ( 35 ) and lung adenocarcinoma may have solid, papillary, or acinar growth patterns ( 36 ). Since epithelial cells contain keratins as intermediate filaments and keratin antibodies are widely used to identify tumors of epithelial origin ( 37 ) being expressed in up to 93% of carcinomas ( 38 ), an antibody cocktail that recognize acidic and basic cytokeratins [pancytokeratin (panCK)] is the standard biomarker to highlight epithelial cells in mIF approaches including DSP.…”

Section: Profiling Of Different Types Of Tumors Using Dspmentioning

confidence: 99%

Challenges and Opportunities for Immunoprofiling Using a Spatial High-Plex Technology: The NanoString GeoMx® Digital Spatial Profiler

et al. 2022

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Characterization of the tumor microenvironment through immunoprofiling has become an essential resource for the understanding of the complex immune cell interactions and the assessment of biomarkers for prognosis and prediction of immunotherapy response; however, these studies are often limited by tissue heterogeneity and sample size. The nanoString GeoMx® Digital Spatial Profiler (DSP) is a platform that allows high-plex profiling at the protein and RNA level, providing spatial and temporal assessment of tumors in frozen or formalin-fixed paraffin-embedded limited tissue sample. Recently, high-impact studies have shown the feasibility of using this technology to identify biomarkers in different settings, including predictive biomarkers for immunotherapy in different tumor types. These studies showed that compared to other multiplex and high-plex platforms, the DSP can interrogate a higher number of biomarkers with higher throughput; however, it does not provide single-cell resolution, including co-expression of biomarker or spatial information at the single-cell level. In this review, we will describe the technical overview of the platform, present current evidence of the advantages and limitations of the applications of this technology, and provide important considerations for the experimental design for translational immune-oncology research using this tissue-based high-plex profiling approach.

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Section: Profiling Of Different Types Of Tumors Using Dspmentioning

confidence: 99%

Challenges and Opportunities for Immunoprofiling Using a Spatial High-Plex Technology: The NanoString GeoMx® Digital Spatial Profiler

et al. 2022

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“…Lung cancer incidence and mortality are associated with factors such as the Human Development Index (HDI), gross domestic product (GDP), and smoking frequency (1). Based on pathological types, lung cancer can be broadly categorized into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), of which NSCLC is mainly squamous cell carcinoma and adenocarcinoma; adenocarcinoma occupies 30-40% of lung cancer (2). Since 2010, with advances in diagnosis and surgery, such as standardized division of pathological stages, improvement in thoracoscopic surgery, drug therapy for driver mutations, and application of immune checkpoint inhibitors, the survival rate of patients with non-small cell lung cancer has significantly improved (3)(4)(5)(6)(7)(8).…”

Section: Introductionmentioning

confidence: 99%

Clinical application of common inflammatory and nutritional indicators before treatment in prognosis evaluation of non-small cell lung cancer: a retrospective real-world study

Zou

et al. 2023

Front. Med.

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ObjectiveTo evaluate the prognostic value of common clinical inflammatory and nutritional indicators before treatment in patients with non-small cell lung cancer in the real world.MethodA total of 5,239 patients with pathologically confirmed non-small cell lung cancer from 2011 to 2018 in the Affiliated Cancer Hospital of Xinjiang Medical University were selected. Their inflammatory and nutritional indicators (RDW, PDW, NLR, LMR, NMR, PLR, SII, PNI, TP, ALB, CYRFA21-1, CEA, CA125, NSE, α1-globulin, α2-globulin, β1-globulin, β2-globulin, and γ-globulin) before treatment were collected. From the total number, 1,049 patients were randomly sampled (18 to 20% of patients each year) and used as the validation set; the remaining 4,190 patients were used as the training set. According to the eighth edition of the guidelines for the diagnosis, treatment, and stage risk stratification of lung cancer, the patients were divided into four groups: stage I/II operable, stage III operable, stage III inoperable, and stage IV. We used the X-tile software to intercept and classify the cut-off values of each index in the validation set. Univariate and multivariate Cox proportional-hazard regression were used to screen the independent risk factors affecting the prognosis of non-small cell lung cancer and establish a prognostic model for 1, 3, and 5 years. The validation set was used to verify its performance. Finally, the Kaplan–Meier curve was used to assess the survival rate, and the corresponding nomogram was established for clinical use.ResultsAfter screening, no effective indicators were found in the stage I/II operable group. RDW and CA125 were effective indicators for the stage III operable group (cut-off values were 14.1 and 9.21, respectively, compared with the low-value group; univariate HR was 2.145 and 1.612, and multivariate HR was 1.491 and 1.691, respectively). CYRFA21-1 and CA125 were effective prognostic indicators for the stage III inoperable group (cut-off values were 10.62 and 44.10, respectively, compared with the low-value group; univariate HR was 1.744 and 1.342, and multivariate HR was 1.284 and 1.304, respectively). CYRFA21-1, CA125, NLR, and α1-globulin were effective indicators of prognosis in stage IV (cut-off values were 3.07, 69.60, 4.08, and 5.30, respectively, compared with the low-value group; univariate HR was 1.713, 1.339, 1.388, and 1.539; and multivariate HR was 1.407, 1.119, 1.191, and 1.110, respectively). The model was constructed with the best validation power in stage IV patients (C-index = 0.733, 0.749, and 0.75 at 1, 3, and 5 years, respectively).ConclusionFor patients with stage III and IV non-small cell lung cancer, some inflammatory markers, serum tumor markers, and nutritional indicators are independent prognostic factors. Combined with the general data of patients, the constructed prognostic evaluation model has the best efficacy in patients with stage IV and can be widely used in clinical practice.

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Different pulmonary adenocarcinoma growth patterns significantly affect survival

Cited by 2 publications

References 32 publications

Challenges and Opportunities for Immunoprofiling Using a Spatial High-Plex Technology: The NanoString GeoMx® Digital Spatial Profiler

Challenges and Opportunities for Immunoprofiling Using a Spatial High-Plex Technology: The NanoString GeoMx® Digital Spatial Profiler

Clinical application of common inflammatory and nutritional indicators before treatment in prognosis evaluation of non-small cell lung cancer: a retrospective real-world study

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