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.

Hexavalent chromium exposure activates the non-canonical nuclear factor kappa B pathway to promote immune checkpoint protein programmed death-ligand 1 expression and lung carcinogenesis.

Lung cancer is the leading cause of cancer-related death worldwide; however, the mechanism of lung carcinogenesis has not been clearly defined. Chronic exposure to hexavalent chromium [Cr(VI)], a common environmental and occupational pollutant, causes lung cancer, representing an important lung cancer etiology factor. The mechanism of how chronic Cr(VI) exposure causes lung cancer remains largely unknown. By using cell culture and mouse models and bioinformatics analyses of human lung cancer gene expression profiles, this study investigated the mechanism of Cr(VI)-induced lung carcinogenesis. A new mouse model of Cr(VI)-induced lung carcinogenesis was developed as evidenced by the findings showing that a 16-week Cr(VI) exposure (CaCrO4, 100 µg per mouse once per week) via oropharyngeal aspiration induced lung adenocarcinomas in male and female A/J mice, whereas none of the sham-exposed control mice had lung tumors. Mechanistic studies revealed that chronic Cr(VI) exposure activated the non-canonical NFκB pathway through the long non-coding RNA (lncRNA) ABHD11-AS1/deubiquitinase USP15-mediated tumor necrosis factor receptor-associated factor 3 (TRAF3) down-regulation. The non-canonical NFκB pathway activation increased the interleukin 6 (IL-6)/Janus kinase (Jak)/signal transducer and activator of transcription 3 (Stat3) signaling. The activation of the IL-6/Jak signaling axis by Cr(VI) exposure not only promoted inflammation but also stabilized the immune checkpoint molecule programmed death-ligand 1 (PD-L1) protein in the lungs, reducing T lymphocyte infiltration to the lungs. Given the well-recognized critical role of PD-L1 in inhibiting anti-tumor immunity, these findings suggested that the lncRNA ABHD11-AS1-mediated non-canonical NFκB pathway activation and PD-L1 up-regulation may play important roles in Cr(VI)-induced lung carcinogenesis.

Intestinal IL-22RA1 signaling regulates intrinsic and systemic lipid and glucose metabolism to alleviate obesity-associated disorders.

IL-22 is critical for ameliorating obesity-induced metabolic disorders. However, it is unknown where IL-22 acts to mediate these outcomes. Here we examine the importance of tissue-specific IL-22RA1 signaling in mediating long-term high fat diet (HFD) driven metabolic disorders. To do so, we generated intestinal epithelium-, liver-, and white adipose tissue (WAT)-specific Il22ra1 knockout and littermate control mice. Intestinal epithelium- and liver-specific IL-22RA1 signaling upregulated systemic glucose metabolism. Intestinal IL-22RA1 signaling also mediated liver and WAT metabolism in a microbiota-dependent manner. We identified an association between Oscillibacter and elevated WAT inflammation, likely induced by Mmp12 expressing macrophages. Mechanistically, transcription of intestinal lipid metabolism genes is regulated by IL-22 and potentially IL-22-induced IL-18. Lastly, we show that Paneth cell-specific IL-22RA1 signaling, in part, mediates systemic glucose metabolism after HFD. Overall, these results elucidate a key role of intestinal epithelium-specific IL-22RA1 signaling in regulating intestinal metabolism and alleviating systemic obesity-associated disorders.

Morphologic Severity of Atypia Is Predictive of Lung Cancer Diagnosis.

In cytologic analysis of lung nodules, specimens classified as atypia cannot be definitively diagnosed as benign or malignant. Atypia patients are typically subject to additional procedures to obtain repeat samples, thus delaying diagnosis. We evaluate morphologic categories predictive of lung cancer in atypia patients. This retrospective study stratified patients evaluated for primary lung nodules based on cytologic diagnoses. Atypia patients were further stratified based on the most severe verbiage used to describe the atypical cytology. Logistic regressions and receiver operator characteristic curves were performed. Of 129 patients with cytologic atypia, 62.8% later had cytologically or histologically confirmed lung cancer and 37.2% had benign respiratory processes. Atypia severity significantly predicted final diagnosis even while controlling for pack years and modified Herder score (p = 0.012). Pack years, atypia severity, and modified Herder score predicted final diagnosis independently and while adjusting for covariates (all p < 0.001). This model generated a significantly improved area under the curve compared to pack years, atypia severity, and modified Herder score (all p < 0.001) alone. Patients with severe atypia may benefit from repeat sampling for cytologic confirmation within one month due to high likelihood of malignancy, while those with milder atypia may be followed clinically.

Dry heat sterilization as a method to recycle N95 respirator masks: The importance of fit.

In times of crisis, including the current COVID-19 pandemic, the supply chain of filtering facepiece respirators, such as N95 respirators, are disrupted. To combat shortages of N95 respirators, many institutions were forced to decontaminate and reuse respirators. While several reports have evaluated the impact on filtration as a measurement of preservation of respirator function after decontamination, the equally important fact of maintaining proper fit to the users' face has been understudied. In the current study, we demonstrate the complete inactivation of SARS-CoV-2 and preservation of fit test performance of N95 respirators following treatment with dry heat. We apply scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDS), X-ray diffraction (XRD) measurements, Raman spectroscopy, and contact angle measurements to analyze filter material changes as a consequence of different decontamination treatments. We further compared the integrity of the respirator after autoclaving versus dry heat treatment via quantitative fit testing and found that autoclaving, but not dry heat, causes the fit of the respirator onto the users face to fail, thereby rendering the decontaminated respirator unusable. Our findings highlight the importance to account for both efficacy of disinfection and mask fit when reprocessing respirators to for clinical redeployment.

Intratumoral Budding and Tumor Microenvironment in Pretreatment Rectal Cancer Biopsies Predict the Response to Neoadjuvant Chemoradiotherapy.

Tumor budding at the invasive tumor front (peritumoral budding) is an established prognostic factor in colorectal cancer. However, the significance of intratumoral budding (ITB) in pretreatment biopsies is still uncertain. Our study aims to investigate the association of ITB and tumor microenvironment in pretreatment rectal cancer biopsies with pathologic response to neoadjuvant chemoradiotherapy. Pretreatment biopsies of low-grade rectal cancer from 37 patients who underwent resection after neoadjuvant chemoradiotherapy were retrospectively reviewed to evaluate ITB, type of tumor stroma, and intraepithelial lymphocytes. ITB was counted on a single hotspot in 1 HPF upon pan-keratin immunohistochemical staining. Intraepithelial lymphocytes was graded semiquantitatively as "absent" (≤2/HPF) or "present" (>2/HPF). The tumor stroma was classified as either immature type or maturing type. In pretreatment biopsies, ITB was observed in 34/37 patients (92%). High-grade ITB was significantly associated with a poor pathologic response to neoadjuvant chemoradiotherapy (tumor regression score 2 to 3, P<0.001; and higher posttreatment T stage, P=0.002). Immature type of stroma was significantly associated with both high-grade ITB in biopsies (P=0.02) and a poor pathologic response to neoadjuvant chemoradiotherapy (tumor regression score 2 to 3, P=0.005). In multivariate analysis, ITB and the type of stroma remained the significant parameters for prediction of response to neoadjuvant treatment. Our study indicates that ITB and tumor microenvironment in pretreatment biopsies are strong predictors of response to neoadjuvant chemoradiotherapy, which may assist risk stratification and clinical management in rectal cancer patients.

Dissecting the Oncogenic Roles of Keratin 17 in the Hallmarks of Cancer.

There is an unmet need to identify and validate tumor-specific therapeutic targets to enable more effective treatments for cancer. Heterogeneity in patient clinical characteristics as well as biological and genetic features of tumors present major challenges for the optimization of therapeutic interventions, including the development of novel and more effective precision medicine. The expression of keratin 17 (K17) is a hallmark of the most aggressive forms of cancer across a wide range of anatomical sites and histological types. K17 correlates with shorter patient survival, predicts resistance to specific chemotherapeutic agents, and harbors functional domains that suggest it could be therapeutically targeted. Here, we explore the role of K17 in the hallmarks of cancer and summarize evidence to date for K17-mediated mechanisms involved in each hallmark, elucidating functional roles that warrant further investigation to guide the development of novel therapeutic strategies.

Keratin 17 Is a Novel Cytologic Biomarker for Urothelial Carcinoma Diagnosis.

OBJECTIVES: The microscopic features of urine cytology specimens are subjective and may not reliably distinguish between benign urothelial cells and low-grade urothelial carcinoma (UC). Prior studies demonstrated that keratin 17 (K17) detection in biopsies is highly sensitive for UC. The current study aimed to define K17 diagnostic test performance for initial screening and detect recurrent UC in urine specimens. METHODS: K17 was detected by immunocytochemistry (ICC) in consecutively collected urine specimens (2018-2019). A qualitative score for the K17 test was determined in 81 samples (discovery cohort) and validated in 98 samples (validation cohort). K17 sensitivity and specificity were analyzed in both cohorts across all grades of UC. RESULTS: Based on the discovery cohort, the presence of 5 or more K17 immunoreactive urothelial cells (area under the curve = 0.90; P < .001) was the optimal threshold to define a K17-positive test. The sensitivity of the K17 ICC test for biopsy-confirmed UC was 35 of 36 (97%) and 18 of 21 (86%) in the discovery and validation cohorts, respectively. K17 was positive in 16 of 19 (84%) specimens with biopsy-confirmed low-grade UC and in 34 of 34 (100%) of specimens with high-grade UC. CONCLUSIONS: K17 ICC is a highly sensitive diagnostic test for initial screening and detection of recurrence across all grades of UC.

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.

The New York State SARS-CoV-2 Testing Consortium: Regional Communication in Response to the COVID-19 Pandemic.

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2, created an unprecedented need for comprehensive laboratory testing of populations, in order to meet the needs of medical practice and to guide the management and functioning of our society. With the greater New York metropolitan area as an epicenter of this pandemic beginning in March 2020, a consortium of laboratory leaders from the assembled New York academic medical institutions was formed to help identify and solve the challenges of deploying testing. This report brings forward the experience of this consortium, based on the real-world challenges which we encountered in testing patients and in supporting the recovery effort to reestablish the health care workplace. In coordination with the Greater New York Hospital Association and with the public health laboratory of New York State, this consortium communicated with state leadership to help inform public decision-making addressing the crisis. Through the length of the pandemic, the consortium has been a critical mechanism for sharing experience and best practices in dealing with issues including the following: instrument platforms, sample sources, test performance, pre- and post-analytical issues, supply chain, institutional testing capacity, pooled testing, biospecimen science, and research. The consortium also has been a mechanism for staying abreast of state and municipal policies and initiatives, and their impact on institutional and laboratory operations. The experience of this consortium may be of value to current and future laboratory professionals and policy-makers alike, in dealing with major events that impact regional laboratory services.

Neutralizing activity to SARS-CoV-2 of convalescent and control plasma used in a randomized controlled trial.

BACKGROUND: There are limited data on the neutralizing activity of convalescent plasma (CP) administered in randomized controlled trials (RCT) of COVID-19 infection. STUDY DESIGN AND METHODS: As part of an RCT, CP was collected per FDA guidelines from individuals recovered from COVID-19 infection. CP donors had to have ≥145 optical density (OD) units (ideal target ≥300) using a semiquantitative, immunochromatographic test for IgG antibody to the nucleocapsid protein (NP) of SARS-CoV-2 (typical range 0-500 OD units). A random subset of samples [14 control plasma, 12 CP "medium-anti-NP" (145-299 OD units), and 13 CP "high" anti-NP (≥300 OD units)] were tested for neutralizing antibodies using an established viral luciferase antibody inhibition assay to detect the infection of SARS-CoV-2 pseudovirus that encoded spike protein (SARS2-Strunc ) on a human immunodeficiency virus 1 vector (NL43dEnvNanoLuc), using ACE2-expressing 293 T cells. The titer needed to neutralize 50% of viral activity (NT50) was calculated. RESULTS: The uptake of SARS-CoV-2 pseudovirus by 293TACE2 cells was inhibited by pretreatment with CP compared to control CP (p < .001) with control plasma having a median (IQR) 50% neutralization titer (NT50) of 1:28 (1:16,1:36) compared to 1:334 (1:130,1:1295) and 1:324 (1:244,1:578), for medium anti-NP and high anti-NP CP units, respectively. The neutralizing activity of CP met minimum FDA criteria with neutralizing antibody titers >1:80 in 100% of randomly selected samples, using a conservative approach that excluded non-specific binding. DISCUSSION: Plasma from donors screened using an immunochromatographic test for IgG antibody to SARS-CoV-2 NP exhibited neutralizing activity meeting FDA's minimum standard in all randomly selected COVID-19 CP units.

Keratin 17 Expression Predicts Poor Clinical Outcome in Patients With Advanced Esophageal Squamous Cell Carcinoma.

The major roles of keratin 17 (K17) as a prognostic biomarker have been highlighted in a range of human malignancies. However, its relevance to esophageal squamous cell carcinoma (ESCC) remains unexplored. In this study, the relationship between K17 expression and clinicopathologic parameters and survival were determined by RNA sequencing (RNA-Seq) in 90 ESCCs and by immunohistochemistry (IHC) in 68 ESCCs. K17 expression was significantly higher in ESCC than in paired normal tissues at both the messenger RNA and protein levels. K17 messenger RNA and staining by IHC were significantly correlated with aggressive characteristics, including advanced clinical stage, invasion depth, and lymph node metastases; and were predictive of poor prognosis in advanced disease patients. Furthermore, K17 expression was detected by IHC in high-grade premalignant lesions of the esophageal mucosa, suggesting that K17 could also be a biomarker of dysplasia of the esophageal mucosa. Overall, this study established that K17 is a negative prognostic biomarker for the most common subtype of esophageal cancer.

IL-22 receptor signaling in Paneth cells is critical for their maturation, microbiota colonization, Th17-related immune responses, and anti-Salmonella immunity.

Interleukin-22 (IL-22) signaling in the intestines is critical for promoting tissue-protective functions. However, since a diverse array of cell types (absorptive and secretory epithelium as well as stem cells) express IL-22Ra1, a receptor for IL-22, it has been difficult to determine what cell type(s) specifically respond to IL-22 to mediate intestinal mucosal host defense. Here, we report that IL-22 signaling in the small intestine is positively correlated with Paneth cell differentiation programs. Our Il22Ra1fl/fl;Lgr5-EGFP-creERT2-specific knockout mice and, independently, our lineage-tracing findings rule out the involvement of Lgr5+ intestinal stem cell (ISC)-dependent IL-22Ra1 signaling in regulating the lineage commitment of epithelial cells, including Paneth cells. Using novel Paneth cell-specific IL-22Ra1 knockout mice (Il22Ra1fl/fl;Defa6-cre), we show that IL-22 signaling in Paneth cells is required for small intestinal host defense. We show that Paneth cell maturation, antimicrobial effector function, expression of specific WNTs, and organoid morphogenesis are dependent on cell-intrinsic IL-22Ra1 signaling. Furthermore, IL-22 signaling in Paneth cells regulates the intestinal commensal bacteria and microbiota-dependent IL-17A immune responses. Finally, we show ISC and, independently, Paneth cell-specific IL-22Ra1 signaling are critical for providing immunity against Salmonella enterica serovar Typhimurium. Collectively, our findings illustrate a previously unknown role of IL-22 in Paneth cell-mediated small intestinal host defense.

Publisher Correction to: Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images.

An amendment to this paper has been published and can be accessed via the original article.

Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images.

BACKGROUND: Multiplex immunohistochemistry (mIHC) permits the labeling of six or more distinct cell types within a single histologic tissue section. The classification of each cell type requires detection of the unique colored chromogens localized to cells expressing biomarkers of interest. The most comprehensive and reproducible method to evaluate such slides is to employ digital pathology and image analysis pipelines to whole-slide images (WSIs). Our suite of deep learning tools quantitatively evaluates the expression of six biomarkers in mIHC WSIs. These methods address the current lack of readily available methods to evaluate more than four biomarkers and circumvent the need for specialized instrumentation to spectrally separate different colors. The use case application for our methods is a study that investigates tumor immune interactions in pancreatic ductal adenocarcinoma (PDAC) with a customized mIHC panel. METHODS: Six different colored chromogens were utilized to label T-cells (CD3, CD4, CD8), B-cells (CD20), macrophages (CD16), and tumor cells (K17) in formalin-fixed paraffin-embedded (FFPE) PDAC tissue sections. We leveraged pathologist annotations to develop complementary deep learning-based methods: (1) ColorAE is a deep autoencoder which segments stained objects based on color; (2) U-Net is a convolutional neural network (CNN) trained to segment cells based on color, texture and shape; and ensemble methods that employ both ColorAE and U-Net, collectively referred to as (3) ColorAE:U-Net. We assessed the performance of our methods using: structural similarity and DICE score to evaluate segmentation results of ColorAE against traditional color deconvolution; F1 score, sensitivity, positive predictive value, and DICE score to evaluate the predictions from ColorAE, U-Net, and ColorAE:U-Net ensemble methods against pathologist-generated ground truth. We then used prediction results for spatial analysis (nearest neighbor). RESULTS: We observed that (1) the performance of ColorAE is comparable to traditional color deconvolution for single-stain IHC images (note: traditional color deconvolution cannot be used for mIHC); (2) ColorAE and U-Net are complementary methods that detect 6 different classes of cells with comparable performance; (3) combinations of ColorAE and U-Net into ensemble methods outperform using either ColorAE and U-Net alone; and (4) ColorAE:U-Net ensemble methods can be employed for detailed analysis of the tumor microenvironment (TME). We developed a suite of scalable deep learning methods to analyze 6 distinctly labeled cell populations in mIHC WSIs. We evaluated our methods and found that they reliably detected and classified cells in the PDAC tumor microenvironment. We also present a use case, wherein we apply the ColorAE:U-Net ensemble method across 3 mIHC WSIs and use the predictions to quantify all stained cell populations and perform nearest neighbor spatial analysis. Thus, we provide proof of concept that these methods can be employed to quantitatively describe the spatial distribution immune cells within the tumor microenvironment. These complementary deep learning methods are readily deployable for use in clinical research studies.

Altered RNA Splicing by Mutant p53 Activates Oncogenic RAS Signaling in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is driven by co-existing mutations in KRAS and TP53. However, how these mutations collaborate to promote this cancer is unknown. Here, we uncover sequence-specific changes in RNA splicing enforced by mutant p53 which enhance KRAS activity. Mutant p53 increases expression of splicing regulator hnRNPK to promote inclusion of cytosine-rich exons within GTPase-activating proteins (GAPs), negative regulators of RAS family members. Mutant p53-enforced GAP isoforms lose cell membrane association, leading to heightened KRAS activity. Preventing cytosine-rich exon inclusion in mutant KRAS/p53 PDACs decreases tumor growth. Moreover, mutant p53 PDACs are sensitized to inhibition of splicing via spliceosome inhibitors. These data provide insight into co-enrichment of KRAS and p53 mutations and therapeutics targeting this mechanism in PDAC.

An unbiased high-throughput drug screen reveals a potential therapeutic vulnerability in the most lethal molecular subtype of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is predicted to become the second leading cause of cancer-related deaths in the United States by 2020, due in part to innate resistance to widely used chemotherapeutic agents and limited knowledge about key molecular factors that drive tumor aggression. We previously reported a novel negative prognostic biomarker, keratin 17 (K17), whose overexpression in cancer results in shortened patient survival. In this study, we aimed to determine the predictive value of K17 and explore the therapeutic vulnerability in K17-expressing PDAC, using an unbiased high-throughput drug screen. Patient-derived data analysis showed that K17 expression correlates with resistance to gemcitabine (Gem). In multiple in vitro and in vivo models of PDAC, spanning human and murine PDAC cells, and orthotopic xenografts, we determined that the expression of K17 results in a more than twofold increase in resistance to Gem and 5-fluorouracil, key components of current standard-of-care chemotherapeutic regimens. Furthermore, through an unbiased drug screen, we discovered that podophyllotoxin (PPT), a microtubule inhibitor, showed significantly higher sensitivity in K17-positive compared to K17-negative PDAC cell lines and animal models. In the clinic, another microtubule inhibitor, paclitaxel (PTX), is used in combination with Gem as a first-line chemotherapeutic regimen for PDAC. Surprisingly, we found that when combined with Gem, PPT, but not PTX, was synergistic in inhibiting the viability of K17-expressing PDAC cells. Importantly, in preclinical models, PPT in combination with Gem effectively decreased tumor growth and enhanced the survival of mice bearing K17-expressing tumors. This provides evidence that PPT and its derivatives could potentially be combined with Gem to enhance treatment efficacy for the ~ 50% of PDACs that express high levels of K17. In summary, we reported that K17 is a novel target for developing a biomarker-based personalized treatment for PDAC.

Correction: Direct therapeutic targeting of immune checkpoint PD-1 in pancreatic cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Overview of established and emerging immunohistochemical biomarkers and their role in correlative studies in MRI.

Clinical practice in radiology and pathology requires professional expertise and many years of training to visually evaluate and interpret abnormal phenotypic features in medical images and tissue sections to generate diagnoses that guide patient management and treatment. Recent advances in digital image analysis methods and machine learning have led to significant interest in extracting additional information from medical and digital whole-slide images in radiology and pathology, respectively. This has led to significant interest and research in radiomics and pathomics to correlate phenotypic features of disease with image analytics in order to identify image-based biomarkers. The expanding role of big data in radiology and pathology parallels the development and role of immunohistochemistry (IHC) in the daily practice of pathology. IHC methods were initially developed to provide additional information to help classify tumors and then transformed into an indispensable tool to guide treatment in many types of cancer. IHC markers are used in daily practice to identify specific types of cells and highlight their distributions in tissues in order to distinguish benign from neoplastic cells, determine tumor origin, subclassify neoplasms, and support and confirm diagnoses. In this regard, radiomics, pathomics, and IHC methods are very similar since they enable the extraction of image-based features to characterize various properties of diseases. Due to the dramatic advancements in recent radiomics research, we provide a brief overview of the role of established and emerging IHC biomarkers in various tumor types that have been correlated with radiologic biomarkers to improve diagnostic accuracy, predict prognosis, guide patient management, and select treatment strategies. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:341-354.