Dysregulated epithelial to mesenchymal transition (EMT) in cancer cells endows invasive and metastatic properties upon cancer cells that favor successful colonization of distal target organs and therefore play a critical role in transforming early‐stage carcinomas into invasive malignancies. EMT has also been associated with tumor recurrence and drug resistance and cancer stem cell initiation. Therefore, better understanding of the mechanisms behind EMT could ultimately contribute to the development of novel prognostic approaches and individualized therapies that specifically target EMT processes. As an effort to characterize the central transcriptome changes during EMT, we have developed a Transforming growth factor (TGF)‐beta‐based in vitro EMT model and used it to profile EMT‐related gene transcriptional changes in two different cell lines, a non‐small cell lung cancer cell line H358, and a breast cell line MCF10a. After 7 days of TGF‐beta/Oncostatin M (OSM) treatment, changes in cell morphology to a mesenchymal phenotype were observed as well as concordant EMT‐associated changes in mRNA and protein expression. Further, increased motility was noted and flow cytometry confirmed enrichment in cancer stem cell‐like populations. Microarray‐based differential expression analysis identified an EMT‐associated gene expression signature which was confirmed by RT‐qPCR and which significantly overlapped with a previously published EMT core signature. Finally, two novel EMT‐regulating transcription factors, IRF5 and LMCD1, were identified and independently validated.

By performing an integrative radiogenomic analysis by using independent data sets with imaging, outcomes, and gene expression in tandem with both in silico and functional in vitro analysis, we are able to provide multilevel biological support for an association between fluoro-2-deoxyglucose PET, poor outcome, and epithelial-mesenchymal transition in non–small cell lung cancer. PurposeTo investigate whether non–small cell lung cancer (NSCLC) tumors that express high normalized maximum standardized uptake value (SUVmax) are associated with a more epithelial-mesenchymal transition (EMT)–like phenotype.Materials and MethodsIn this institutional review board–approved study, a public NSCLC data set that contained fluorine 18 (18F) fluoro-2-deoxyglucose positron emission tomography (PET) and messenger RNA expression profile data (n = 26) was obtained, and patients were categorized on the basis of measured normalized SUVmax values. Significance analysis of microarrays was then used to create a radiogenomic signature. The prognostic ability of this signature was assessed in a second independent data set that consisted of clinical and messenger RNA expression data (n = 166). Signature concordance with EMT was evaluated by means of validation in a publicly available cell line data set. Finally, by establishing an in vitro EMT lung cancer cell line model, an attempt was made to substantiat...

This integrative study showed cancer-related mutations within multiple microenvironments of prostate glands including regions found via histologic analysis to be normal and abnormal (ie, high grade... PurposeTo assess the underlying genomic variation of prostate gland microenvironments of patients with prostate adenocarcinoma in the context of colocalized multiparametric magnetic resonance (MR) ...

Large language models showed interpretative reasoning in solving diagnostically challenging medical cases.

Results compiled from 17 data sets and more than 3000 patients with breast cancer reveal that image biomarkers aiming to capture the intrinsic molecular subtypes that are based on receptor-based surrogates rather than the actual molecular subtypes show poor overall accuracy and concordance. PurposeTo determine the concordance and accuracy of imaging surrogates of immunohistochemical (IHC) markers and the molecular classification of breast cancer.Materials and MethodsA total of 3050 patients from 17 public breast cancer data sets containing IHC marker receptor status (estrogen receptor/progesterone receptor/human epidermal growth factor receptor 2 [HER2]) and their molecular classification (basal-like, HER2-enriched, luminal A or B) were analyzed. Diagnostic accuracy and concordance as measured with the κ statistic were calculated between the IHC and molecular classifications. Simulations were performed to assess the relationship between accuracy of imaging-based IHC markers to predict molecular classification. A simulation was performed to examine effects of misclassification of molecular type on patient survival.ResultsAccuracies of intrinsic subtypes based on IHC subtype were 71.7% (luminal A), 53.7% (luminal B), 64.8% (HER2-enriched), and 81.7% (basal-like). The κ agreement was fair (κ = ...

Chromosomal instability (CIN) of gastric cancer is correlated with distinct outcomes. This study aimed to investigate the role of computed tomography (CT) imaging traits in predicting the CIN status of gastric cancer. We screened 443 patients in the Cancer Genome Atlas gastric cancer cohort to filter 40 patients with complete CT imaging and genomic data as the training cohort. CT imaging traits were subjected to logistic regression to select independent predictors for the CIN status. For the validation cohort, we prospectively enrolled 18 gastric cancer patients for CT and tumor genomic analysis. The imaging predictors were tested in the validation cohort using receiver operating characteristic curve (ROC) analysis. Thirty patients (75%) in the training cohort and 9 patients (50%) in the validation cohort had CIN subtype gastric cancers. Smaller tumor diameter (p = 0.017) and acute tumor transition angle (p = 0.045) independently predict CIN status in the training cohort. In the validation cohort, acute tumor transition angle demonstrated the highest accuracy, sensitivity, and specificity of 88.9%, 88.9%, and 88.9%, respectively, and areas under ROC curve of 0.89. In conclusion, this pilot study showed acute tumor transition angle on CT images may predict the CIN status of gastric cancer.