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. METHODS: Multiplex immunohistochemistry (mIHC) and automated image analysis based on novel computational imaging technology were used to decipher the abundance and spatial distribution of T cells, macrophages, and tumor cells, relative to K17 expression in 235 PDACs. RESULTS: K17 expression had profound effects on the exclusion of intratumoral CD8+ T cells and was also associated with decreased numbers of peritumoral CD8+ T cells, CD16+ macrophages, and CD163+ macrophages (p < 0.0001). The differences in the intratumor and peritumoral CD8+ T cell abundance were not impacted by neoadjuvant therapy, tumor stage, grade, lymph node status, histologic subtype, nor KRAS, p53, SMAD4, or CDKN2A mutations. CONCLUSIONS: Thus, K17 expression correlates with major differences in the immune microenvironment that are independent of any tested clinicopathologic or tumor intrinsic variables, suggesting that targeting K17-mediated immune effects on the immune system could restore the innate immunologic response to PDAC and might provide novel opportunities to restore immunotherapeutic approaches for this most deadly form of cancer.

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. RESULTS: Patients with advanced-stage, low K17 PDACs treated using 5-fluorouracil (5-FU)-based chemotherapeutic regimens had 3-fold longer survival than corresponding cases treated with gemcitabine-based chemotherapy. By contrast, PDACs with high K17 did not respond to either regimen. The predictive value of K17 was independent of tumor mutation status and other clinicopathologic variables. CONCLUSIONS: The detection of K17 in 10% or greater of PDAC cells identified patients with shortest survival. Among patients with low K17 PDACs, 5-FU-based treatment was more likely than gemcitabine-based therapies to extend survival.

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. Methods: Multiplex immunohistochemistry (mIHC) and automated image analysis based on novel computational imaging technology were used to decipher the abundance and spatial distribution of T cells, macrophages, and tumor cells, relative to K17 expression in 235 PDACs. Results: K17 expression had profound effects on the exclusion of intratumoral CD8 + T cells and was also associated with decreased numbers of peritumoral CD8 + T cells, CD16 + macrophages, and CD163 + macrophages (p < 0.0001). The differences in the intratumor and peritumoral CD8 + T cell abundance were not impacted by neoadjuvant therapy, tumor stage, grade, lymph node status, histologic subtype, nor KRAS, p53, SMAD4, or CDKN2A mutations. Conclusions: Thus, K17 expression correlates with major differences in the immune microenvironment that are independent of any tested clinicopathologic or tumor intrinsic variables, suggesting that targeting K17-mediated immune effects on the immune system could restore the innate immunologic response to PDAC and might provide novel opportunities to restore immunotherapeutic approaches for this most deadly form of cancer.

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). The aims of this study were to determine whether there was a correlation in K17 scores detected in matched NABs and surgical resection tissue sections and whether K17 IHC in NAB cell block specimens could be used as a negative prognostic biomarker in PDAC. METHODS: K17 IHC was performed for a cohort of 70 patients who had matched NAB cell block and surgical resection samples to analyze the correlation of K17 expression levels. K17 IHC was also performed in cell blocks from discovery and validation cohorts. Kaplan-Meier and Cox proportional hazards regression models were analyzed to determine survival differences in cases with different levels of K17 IHC expression. RESULTS: K17 IHC expression correlated in matched NABs and resection tissues. NAB samples were classified as high for K17 when ≥80% of tumor cells showed strong (2+) staining. High-K17 cases, including stage-matched cases, had shorter survival. CONCLUSIONS: K17 has been identified as a robust and independent prognostic biomarker that stratifies clinical outcomes for cases that are diagnosed by NAB. Testing for K17 also has the potential to inform clinical decisions for optimization of chemotherapeutic interventions.

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. Gene expression data (mRNA) from The Cancer Genome Atlas were analyzed for 271 high-grade endometrial carcinomas and K17 immunohistochemistry (IHC) was performed on a separate cohort of 119 high-grade endometrial cancer cases from two academic medical centers. Survival analyses were determined by Cox proportional hazards regression. High K17 mRNA and IHC correlated with decreased overall survival (HR: 1.8, P = .0101, HR: 1.8, P = .0488, respectively). K17 was positive in malignant glandular cells of the endometrium but not in other tissues, including endometrial stroma, myometrium and uterine sarcoma. These results support the conclusion that K17 is a negative prognostic biomarker in high-grade endometrial carcinoma and that K17 IHC test results could be used to inform decisions related to therapeutic intervention.

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. Here, we set out to determine if K17 is as accurate as molecular subtyping of PDAC to identify patients with the shortest survival. K17 mRNA was analyzed in two independent PDAC cohorts for discovery (n = 124) and validation (n = 145). Immunohistochemical localization and scoring of K17 immunohistochemistry (IHC) was performed in a third independent cohort (n = 74). Kaplan-Meier and Cox proportional-hazard regression models were analyzed to determine cancer specific survival differences in low vs. high mRNA K17 expressing cases. We established that K17 expression in PDACs defines the most aggressive form of the disease. By using Cox proportional hazard ratio, we found that increased expression of K17 at the IHC level is also associated with decreased survival of PDAC patients. Additionally, within PDACs of advanced stage and negative surgical margins, K17 at both mRNA and IHC level is sufficient to identify the subgroup with the shortest survival. These results identify K17 as a novel negative prognostic biomarker that could inform patient management decisions.

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. A threshold was established to dichotomize K17 status in tissue specimens as positive vs. negative, based on the proportion of cells that showed strong staining. In addition, K17 immunocytochemistry was performed on urine cytology slides, scoring positive test results based on the detection of K17 in any urothelial cells. Mann-Whitney and receiver operating characteristic analyses were used to compare K17 expression between histologic diagnostic categories. The median proportion of K17 positive tumor cells was 70% (range 20-90%) in PUNLMP, 30% (range 5-100%) in PUC-LG, 20% (range 1-100%), in PUC-HG, 35% (range 5-100%) in UC but staining was rarely detected (range 0-10%) in normal urothelial mucosa. Defining cases in which K17 was detected in ≥10% of cells were considered positive, the sensitivity of K17 in biopsies was 89% (95% CI: 80-96%) and the specificity was 88% (95% CI: 70-95%) to distinguish malignant lesions (PUC-LG, PUC-HG, and UC) from normal urothelial mucosa. Furthermore, K17 immunocytochemistry had a sensitivity of 100% and a specificity of 96% for urothelial carcinoma in 112 selected urine specimens. Thus, K17 is a sensitive and specific biomarker of urothelial neoplasia in tissue specimens and should be further explored as a novel biomarker for the cytologic diagnosis of urine specimens.

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. We previously determined that Krüppel-like factor 15 (KLF15), a kidney-enriched zinc finger transcription factor, is required for restoring podocyte differentiation markers in mice and human podocytes under cell stress. Here, we show that in vitro treatment with dexamethasone induced a rapid increase of KLF15 expression in human and murine podocytes and enhanced the affinity of glucocorticoid receptor binding to the promoter region of KLF15 In three independent proteinuric murine models, podocyte-specific loss of Klf15 abrogated dexamethasone-induced podocyte recovery. Furthermore, knockdown of KLF15 reduced cell survival and destabilized the actin cytoskeleton in differentiated human podocytes. Conversely, overexpression of KLF15 stabilized the actin cytoskeleton under cell stress in human podocytes. Finally, the level of KLF15 expression in the podocytes and glomeruli from human biopsy specimens correlated with glucocorticoid responsiveness in 35 patients with minimal change disease or primary FSGS. Thus, these studies identify the critical role of KLF15 in mediating the salutary effects of glucocorticoids in the podocyte.

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. Specifically, we determined that K17 functions as an oncoprotein by regulating the subcellular localization and degradation of p27(KIP1). We found that K17 was released from intermediate filaments and translocated into the nucleus via a nuclear localization signal (NLS), specific among keratins, where it bound p27(KIP1) during G1 phase of the cell cycle. p27(KIP1) lacks a nuclear export signal (NES) and requires an adaptor for CRM1 binding for nuclear export. In K17, we defined and validated a leucine-rich NES that mediated CRM1 binding for export. Cervical cancer cells expressing K17 mutations in its NLS or NES signals exhibited an increase in levels of nuclear p27(KIP1), whereas cells expressing wild-type K17 exhibited a depletion in total endogenous p27(KIP1). In clinical specimens of cervical cancer, we confirmed that the expressions of K17 and p27(KIP1) were inversely correlated, both across tumors and within individual tumors. Overall, our findings establish that K17 functions specially among keratins as an oncoprotein by controlling the ability of p27(KIP1) to influence cervical cancer pathogenesis.

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. This novel strategy can be considered as a complex mix of "bottom-up" and "top-down" mechanisms, integrated by calculating a unique index inside each region. The method was evaluated on a set of 338 images in which an expert pathologist had drawn the Regions of Interest. The proposed method outperforms two state-of-the-art methods devised to determine Regions of Interest (RoIs) in natural images. The quality gain with respect to an adaptated Itti's model which found RoIs was 3.6 dB in average, while with respect to the Achanta's proposal was 4.9 dB.

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. Four pathologists with a similar level of experience, graduated from the same pathology program, navigated six virtual slides. Different issues were evaluated, namely, the percentage of common visited image regions, the time spent at each and its coincidence level, that is to say, the region of interest location. In addition, navigation patterns were also assessed, i.e., mouse movement velocities and linearity of the diagnostic paths. Results suggest that regions of interest are determined by a complex combination of the visited area, the time spent at each visit and the coincidence level among pathologists. Additionally, linear trajectories and particular velocity patterns were found for the registered diagnostic paths.