RESUMEN
The increasing detection of colorectal adenomas and early adenocarcinomas (ADCs) in the context of nationwide screening programs has led to a significant increase in the incidence of inconclusive diagnoses in which histopathologic analysis of endoscopic biopsies does not allow pathologists to provide a reliable diagnosis of stromal invasion. The objective of this study was to analyze the discriminative capacity of the immunohistochemical expression of fibroblast activation protein-α (FAP) in distinguishing colorectal adenomas with low-grade dysplasia (LGD) and high-grade dysplasia (HGD) from invasive intestinal-type ADCs. The study analyzed the first endoscopic biopsies from a series of patients classified as inconclusive or conclusive for stromal invasion based on the pathologic report. In total, 30 ADCs, 52 HGDs, and 15 LGDs were included in the study. FAP expression was detected in 23/30 ADCs and was negative in all adenomas with either LGD or HGD features (100% specificity and 76.7% sensitivity, area under the curve=0.883, CI=0.79-0.98). Considering these findings, we conclude that FAP is a potentially useful tool for helping pathologists identify invasive lesions in colorectal endoscopic biopsies, avoiding unnecessary biopsy repetitions.
Asunto(s)
Adenocarcinoma , Esófago de Barrett , Neoplasias Colorrectales , Humanos , Esófago de Barrett/patología , Adenocarcinoma/patología , Biopsia , HiperplasiaRESUMEN
Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique's spatial resolution. However, it cannot yet compete with the superior identification power of high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS), and therefore, very often, the latter is used to refine the assignment of the species detected by LIMS. Also, it is not clear if the differences in sensitivity and spatial resolution between the two techniques lead to a similar panel of biomarkers for a given disease. Here, we explore the capabilities of LIMS and HPLC-MS to produce a panel of lipid biomarkers to screen nephrectomy samples from 40 clear cell renal cell carcinoma patients. The same set of samples was explored by both techniques, and despite the important differences between them in terms of the number of detected and identified species (148 by LIMS and 344 by HPLC-MS in negative-ion mode) and the presence/absence of image capabilities, similar conclusions were reached: using the lipid fingerprint, it is possible to set up classifiers that correctly identify the samples as either healthy or tumor samples. The spatial resolution of LIMS enables extraction of additional information, such as the existence of necrotic areas or the existence of different tumor cell populations, but such information does not seem determinant for the correct classification of the samples, or it may be somehow compensated by the higher analytical power of HPLC-MS. Similar conclusions were reached with two very different techniques, validating their use for the discovery of lipid biomarkers.
Asunto(s)
Carcinoma de Células Renales , Neoplasias Renales , Humanos , Espectrometría de Masa por Láser de Matriz Asistida de Ionización Desorción/métodos , Cromatografía Líquida de Alta Presión/métodos , Lipidómica/métodos , Carcinoma de Células Renales/diagnóstico , Neoplasias Renales/diagnóstico , Lípidos/análisisRESUMEN
For many years, traditional histology has been the gold standard for the diagnosis of many diseases. However, alternative and powerful techniques have appeared in recent years that complement the information extracted from a tissue section. One of the most promising techniques is imaging mass spectrometry applied to lipidomics. Here, we demonstrate the capabilities of this technique to highlight the architectural features of the human kidney at a spatial resolution of 10 µm. Our data demonstrate that up to seven different segments of the nephron and the interstitial tissue can be readily identified in the sections according to their characteristic lipid fingerprints and that such fingerprints are maintained among different individuals (n = 32). These results set the foundation for further studies on the metabolic bases of the diseases affecting the human kidney.