MicroRNA-based assay for differential diagnosis of squamous from non-squamous non-small cell lung carcinoma

11069 Background: Recent advances in biologically directed therapies for non-small cell lung carcinoma (NSCLC) emphasize the need for more accurate sub-classification of NSCLC, as treatment may be dictated by histologic subtype. In particular, squamous histology can be a counter-indication for treatment by VEGF inhibitors. MicroRNAs are highly tissue-specific biomarkers with potential clinical applicability for defining cancer type and origin. MicroRNAs are well preserved in formalin fixed tissue, making them ideal candidates for molecular markers for use in routinely processed material. Here we report on the development and performance of a microRNA-based assay for the differential diagnosis of squamous from non-squamous NSCLC. Methods: We developed protocols for extraction of high-quality RNA that retain the microRNA fraction from FFPE archival tissue samples. MicroRNA microarrays were used to profile more than a hundred NSCLC samples. Specific microRNA qRT-PCR was used to validate results, and to develop a diagnostic assay. Results: We identified a microRNA biomarker that is strongly overexpressed in squamous cell NSCLC. A diagnostic assay (miRview squamous) was developed, that utilizes qRT-PCR measurement of this microRNA, normalized by an additional microRNA and a small nuclear RNA. This assay was validated on a blinded test set of 64 tumor samples, and had sensitivity of 97% and specificity of 91%. More than ¾ of the samples were classified with high confidence, and these classifications were accurate in 96% of the cases. Conclusions: MicroRNAs are becoming an important tool for classification of cancers. A diagnostic assay based on the specificity of a single microRNA accurately identifies squamous from non-squamous NSCLC. This assay provides an important new tool for the classification of NSCLC. [Table: see text]

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Differential development of large-cell neuroendocrine or small-cell lung carcinoma upon inactivation of 4 tumor suppressor genes

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1821745116 ◽

2019 ◽

Vol 116 (44) ◽

pp. 22300-22306 ◽

Cited By ~ 4

Author(s):

Sara Lázaro ◽

Miriam Pérez-Crespo ◽

Corina Lorz ◽

Alejandra Bernardini ◽

Marta Oteo ◽

...

Keyword(s):

Lung Cancer ◽

Lung Carcinoma ◽

Small Cell Lung Carcinoma ◽

Large Cell ◽

Small Cell ◽

Imaging Method ◽

Cancer Type ◽

High Grade ◽

Small Cell Lung ◽

Cell Lung Carcinoma

High-grade neuroendocrine lung malignancies (large-cell neuroendocrine cell carcinoma, LCNEC, and small-cell lung carcinoma, SCLC) are among the most deadly lung cancer conditions with no optimal clinical management. The biological relationships between SCLC and LCNEC are still largely unknown and a current matter of debate as growing molecular data reveal high heterogeneity with potential therapeutic consequences. Here we describe murine models of high-grade neuroendocrine lung carcinomas generated by the loss of 4 tumor suppressors. In an Rbl1-null background, deletion of Rb1, Pten, and Trp53 floxed alleles after Ad-CMVcre infection in a wide variety of lung epithelial cells produces LCNEC. Meanwhile, inactivation of these genes using Ad-K5cre in basal cells leads to the development of SCLC, thus differentially influencing the lung cancer type developed. So far, a defined model of LCNEC has not been reported. Molecular and transcriptomic analyses of both models revealed strong similarities to their human counterparts. In addition, a 68Ga-DOTATOC–based molecular-imaging method provides a tool for detection and monitoring the progression of the cancer. These data offer insight into the biology of SCLC and LCNEC, providing a useful framework for development of compounds and preclinical investigations in accurate immunocompetent models.

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Comparison of Differential Diagnosis of Lung Cancer by Diffuse Weighted Imaging and Sagittal Imaging with Short Inversion Recovery Sequence

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2021.3356 ◽

2021 ◽

Vol 11 (3) ◽

pp. 822-826

Author(s):

Wei Zhang ◽

Qingyu Cai ◽

Guoli Wei

Keyword(s):

Lung Cancer ◽

Differential Diagnosis ◽

Squamous Cell ◽

Lung Carcinoma ◽

Small Cell Lung Carcinoma ◽

Small Cell ◽

Small Cell Lung ◽

Recovery Sequence ◽

Cell Lung Carcinoma ◽

Diagnosis Of Lung Cancer

The differential diagnosis of advanced lung cancer is difficult in clinical practice. Our study aims to compare the value of diffusion weighted imaging (DWI) with short-term inversion recovery sequence (STIR) for sagittal imaging in the differential diagnosis of lung cancer. 149 patients with non-small cell lung carcinoma (NSCLC) were enrolled and underwent DWI and STIR sagittal imaging. To quantify cancer types, we evaluated the apparent diffusion coefficient (ADC) value on DWI and the contrast ratio (CRs) on sagittal imaging. The ADC values of subclasses in NSCLC were significantly higher than small cell lung carcinoma (SCLC) (p <0.01). The mean CRs were 1.59 for SCLC and 1.30 for NSCLC with a significant difference (p < 0.01). Large cell carcinomas (LCC) and adenocarcinomas have significant differences compared to small cell carcinomas (SCC) without difference between squamous cell carcinomas (p > 0.05); this is also the case for CRs. Squamous cell carcinoma and adenocarcinoma have significant differences compared to SCC without difference in LCC (p > 0.05). Qualitative evaluation of the feasible thresholds DWI and STIR showed that the thresholds were 0.9810−3 mm2/s and 1.37 respectively. The specificity and accuracy was 78.5% is 85.3% for DWI, which was significantly higher than STIR (56.3% and 61.0%). The combination of DWI and STIR sequences was superior to DWI alone with an accuracy rate of 94.3%. DWI is more helpful than STIR in differentiating SCLC and NSCLC, and their combined use can significantly improve diagnosis accuracy.

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