Engineered feature embeddings meet deep learning: A novel strategy to improve bone marrow cell classification and model transparency.

Cytomorphology evaluation of bone marrow cell is the initial step to diagnose different hematological diseases. This assessment is still manually performed by trained specialists, who may be a bottleneck within the clinical process. Deep learning algorithms are a promising approach to automate this bone marrow cell evaluation.

Keratin 17 and A2ML1 are negative prognostic biomarkers in non-small cell lung cancer.

Although the overall prognosis for patients with non-small cell lung cancer (NSCLC) has improved over the past several decades, there are still survival differences that are not accurately defined by clinicopathological factors. Thus, there is an unmet clinical need to develop novel approaches to enhance prognostic accuracy for these patients. Keratin 17 (K17) is a negative prognostic biomarker in a wide range of cancer types, including pancreatic ductal adenocarcinoma, head and neck squamous cell carcinoma, and pulmonary adenocarcinoma (LUAD), but has yet to be investigated as a prognostic biomarker in primary lung squamous cell carcinoma (LSCC).

Keratin 17 modulates the immune topography of pancreatic cancer.

Background: The immune microenvironment impacts tumor growth, invasion, metastasis, and patient survival and may provide opportunities for therapeutic intervention in pancreatic ductal adenocarcinoma (PDAC). Although never studied as a potential modulator of the immune response in most cancers, Keratin 17 (K17), a biomarker of the most aggressive (basal) molecular subtype of PDAC, is intimately involved in the histogenesis of the immune response in psoriasis, basal cell carcinoma, and cervical squamous cell carcinoma. Thus, we hypothesized that K17 expression could also impact the immune cell response in PDAC, and that uncovering this relationship could provide insight to guide the development of immunotherapeutic opportunities to extend patient survival.

Keratin 17 is a prognostic and predictive biomarker in pancreatic ductal adenocarcinoma.

Objectives: To determine the role of keratin 17 (K17) as a predictive biomarker for response to chemotherapy by defining thresholds of K17 expression based on immunohistochemical tests that could be used to optimize therapeutic intervention for patients with pancreatic ductal adenocarcinoma (PDAC).

Methods: We profiled K17 expression, a hallmark of the basal molecular subtype of PDAC, by immunohistochemistry in 2 cohorts of formalin-fixed, paraffin-embedded PDACs (n = 305). We determined a K17 threshold of expression to optimize prognostic stratification according to the lowest Akaike information criterion and explored the potential relationship between K17 and chemoresistance by multivariate predictive analyses.

Keratin 17 modulates the immune topography of pancreatic cancer.

Background: The immune microenvironment impacts tumor growth, invasion, metastasis, and patient survival and may provide opportunities for therapeutic intervention in pancreatic ductal adenocarcinoma (PDAC). Although never studied as a potential modulator of the immune response in most cancers, Keratin 17 (K17), a biomarker of the most aggressive (basal) molecular subtype of PDAC, is intimately involved in the histogenesis of the immune response in psoriasis, basal cell carcinoma, and cervical squamous cell carcinoma. Thus, we hypothesized that K17 expression could also impact the immune cell response in PDAC, and that uncovering this relationship could provide insight to guide the development of immunotherapeutic opportunities to extend patient survival.

Keratin 17 testing in pancreatic cancer needle aspiration biopsies predicts survival.

Background: Although pancreatic ductal adenocarcinoma (PDAC) has one of the lowest 5-year survival rates of all cancers, differences in survival exist between patients with clinically identical characteristics. The authors previously demonstrated that keratin 17 (K17) expression in PDAC, measured by RNA sequencing or immunohistochemistry (IHC), is an independent negative prognostic biomarker. Only 20% of cases are candidates for surgical resection, but most patients are diagnosed by needle aspiration biopsy (NAB).

Keratin 17 is a negative prognostic biomarker in high-grade endometrial carcinomas.

Keratin 17 (K17) has been established as a negative prognostic biomarker in cervical and ovarian cancers but has not previously been evaluated as a prognostic biomarker in endometrial adenocarcinoma. The association of K17 with decreased patient survival may be explained in part by the discovery that K17 drives tumor aggression by serving as a nuclear shuttle of p27, leading to cell cycle progression and tumor growth. The current study tests the hypothesis that K17 mRNA and protein levels correlate with decreased survival of patients with high-grade endometrial cancer.

Keratin 17 identifies the most lethal molecular subtype of pancreatic cancer.

Although the overall five-year survival of patients with pancreatic ductal adenocarcinoma (PDAC) is dismal, there are survival differences between cases with clinically and pathologically indistinguishable characteristics, suggesting that there are uncharacterized properties that drive tumor progression. Recent mRNA sequencing studies reported gene-expression signatures that define PDAC molecular subtypes that correlate with differences in survival. We previously identified Keratin 17 (K17) as a negative prognostic biomarker in other cancer types.

Keratin 17 is a sensitive and specific biomarker of urothelial neoplasia.

There is a clinical need to identify novel biomarkers to improve diagnostic accuracy for the detection of urothelial tumors. The current study aimed to evaluate keratin 17 (K17), an oncoprotein that drives cell cycle progression in cancers of multiple anatomic sites, as a diagnostic biomarker of urothelial neoplasia in bladder biopsies and in urine cytology specimens. We evaluated K17 expression by immunohistochemistry in formalin-fixed, paraffin embedded tissue specimens of non-papillary invasive urothelial carcinoma (UC) (classical histological cases), high grade papillary UC (PUC-LG), low grade papillary UC (PUC-HG), papillary urothelial neoplasia of low malignant potential (PUNLMP), and normal bladder mucosa.

Krüppel-Like Factor 15 Mediates Glucocorticoid-Induced Restoration of Podocyte Differentiation Markers.

Podocyte injury is the inciting event in primary glomerulopathies, such as minimal change disease and primary FSGS, and glucocorticoids remain the initial and often, the primary treatment of choice for these glomerulopathies. Because inflammation is not readily apparent in these diseases, understanding the direct effects of glucocorticoids on the podocyte, independent of the immunomodulatory effects, may lead to the identification of targets downstream of glucocorticoids that minimize toxicity without compromising efficacy. Several studies showed that treatment with glucocorticoids restores podocyte differentiation markers and normal ultrastructure and improves cell survival in murine podocytes.

Keratin-17 Promotes p27KIP1 Nuclear Export and Degradation and Offers Potential Prognostic Utility.

Keratins that are overexpressed selectively in human carcinomas may offer diagnostic and prognostic utility. In this study, we show that high expression of keratin-17 (K17) predicts poor outcome in patients with cervical cancer, at early or late stages of disease, surpassing in accuracy either tumor staging or loss of p27(KIP1) as a negative prognostic marker in this setting. We investigated the mechanistic basis for the biologic impact of K17 through loss- and gain-of-function experiments in human cervix, breast, and pancreatic cancer cells.

A supervised visual model for finding regions of interest in basal cell carcinoma images.

This paper introduces a supervised learning method for finding diagnostic regions of interest in histopathological images. The method is based on the cognitive process of visual selection of relevant regions that arises during a pathologist's image examination. The proposed strategy emulates the interaction of the visual cortex areas V1, V2 and V4, being the V1 cortex responsible for assigning local levels of relevance to visual inputs while the V2 cortex gathers together these small regions according to some weights modulated by the V4 cortex, which stores some learned rules.

An experimental study of pathologist's navigation patterns in virtual microscopy.

In virtual microscopy, a sequential process of captures of microscopical fields, allows to construct a virtual slide which is visualized using a specialized software, called the virtual microscopy viewer. This tool allows useful exploration of images, composed of thousands of microscopical fields of view at different levels of magnification, emulating an actual microscopical examination. The aim of this study was to establish the main pathologist's navigation patterns when exploring virtual microscopy slides, using a graphical user interface, adapted to the pathologist's workflow.