Spliceosomal disruption of the non-canonical BAF complex in cancer.

SF3B1 is the most commonly mutated RNA splicing factor in cancer1-4, but the mechanisms by which SF3B1 mutations promote malignancy are poorly understood. Here we integrated pan-cancer splicing analyses with a positive-enrichment CRISPR screen to prioritize splicing alterations that promote tumorigenesis. We report that diverse SF3B1 mutations converge on repression of BRD9, which is a core component of the recently described non-canonical BAF chromatin-remodelling complex that also contains GLTSCR1 and GLTSCR1L5-7. Mutant SF3B1 recognizes an aberrant, deep intronic branchpoint within BRD9 and thereby induces the inclusion of a poison exon that is derived from an endogenous retroviral element and subsequent degradation of BRD9 mRNA. Depletion of BRD9 causes the loss of non-canonical BAF at CTCF-associated loci and promotes melanomagenesis. BRD9 is a potent tumour suppressor in uveal melanoma, such that correcting mis-splicing of BRD9 in SF3B1-mutant cells using antisense oligonucleotides or CRISPR-directed mutagenesis suppresses tumour growth. Our results implicate the disruption of non-canonical BAF in the diverse cancer types that carry SF3B1 mutations and suggest a mechanism-based therapeutic approach for treating these malignancies.

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.

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.

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.

Unmet clinical needs in cervical cancer screening.

Cancer rates worldwide are expected to increase disproportionally in coming decades relative to the projected increase in population, especially in the developing world. The general unavailability of the Pap test and the cost of the HPV test in the developing world have precluded the deployment of effective cervical cancer screening programs in many developing countries. Recent improvements in testing technology arise from a need to overcome the significant limitations of the Pap test and HPV test, but results require first-world technology and validation. Developing countries, where cervical cancer remains one of the most important causes of cancer death, have the greatest need for an affordable, easy-to-use, and highly reliable cancer screening method that can return a diagnosis through efficient laboratory analysis or, more easily, at a woman's point of care. While research, testing, and vaccine improvements in recent years continue to lower the incidence of cervical cancer in some developed countries such as the U.S., HPV testing research needs to do more than test for the presence of virus. The tests must determine the presence and progression of cervical disease. Tests should be more sensitive and specific than Pap tests and Pap-related tests, and should be accurate in more than 90 percent of cases. Tests also need to be low-cost, objective, and easy to perform so screening programs can be widely implemented in developing countries where the need for a better cervical cancer screening test is highest. Such tests may be available through the recent advances in specific biomarkers of cervical cancer and multiplex detection technologies. Development of the next generation of cervical cancer tests that are more specific, sensitive, and informative than the traditional Pap or HPV test will make a significant impact on the reduction of cervical cancer worldwide.

Laminin promotes metalloproteinase-mediated dystroglycan processing to regulate oligodendrocyte progenitor cell proliferation.

The cell surface receptor dystroglycan mediates interactions between oligodendroglia and laminin-211, an extracellular matrix protein that regulates timely oligodendroglial development. However, dystroglycan's precise role in oligodendroglial development and the potential mechanisms to regulate laminin-dystroglycan interactions remain unknown. Here we report that oligodendroglial dystroglycan is cleaved by metalloproteinases, thereby uncoupling oligodendroglia from laminin binding. Dystroglycan cleavage is selectively stimulated by oligodendrocyte progenitor cell attachment to laminin-211, but not laminin-111 or poly-D-lysine. In addition, dystroglycan cleavage occurs most prominently in oligodendrocyte progenitor cells, with limited dystroglycan cleavage observed in differentiating oligodendrocytes. When dystroglycan cleavage is blocked by metalloproteinase inhibitors, oligodendrocyte progenitor cell proliferation is substantially decreased. Conversely, expression of the intracellular portion of cleaved dystroglycan results in increased oligodendrocyte progenitor cell proliferation, suggesting that endogenous dystroglycan cleavage may promote oligodendrocyte progenitor cell cycle progression. Intriguingly, while matrix metalloproteinase-2 and/or -9 have been reported to be responsible for dystroglycan cleavage, we find that these two metalloproteinases are neither necessary nor sufficient for cleavage of oligodendroglial dystroglycan. In summary, laminin-211 stimulates metalloproteinase-mediated dystroglycan cleavage in oligodendrocyte progenitor cells (but not in differentiated oligodendrocytes), which in turn promotes oligodendrocyte progenitor cell proliferation. This novel regulation of oligodendroglial laminin-dystroglycan interactions may have important consequences for oligodendroglial differentiation, both during development and during disease when metalloproteinase levels become elevated.

Keratin 17 in premalignant and malignant squamous lesions of the cervix: proteomic discovery and immunohistochemical validation as a diagnostic and prognostic biomarker.

Most previously described immunohistochemical markers of cervical high-grade squamous intraepithelial lesion (HSIL) and squamous cell carcinoma may help to improve diagnostic accuracy but have a minimal prognostic value. The goals of the current study were to identify and validate novel candidate biomarkers that could potentially improve diagnostic and prognostic accuracy for cervical HSIL and squamous cell carcinoma. Microdissected tissue sections from formalin-fixed paraffin-embedded normal ectocervical squamous mucosa, low-grade squamous intraepithelial lesion (LSIL), HSIL and squamous cell carcinoma sections were analyzed by mass spectrometry-based shotgun proteomics for biomarker discovery. The diagnostic specificity of candidate biomarkers was subsequently evaluated by immunohistochemical analysis of tissue microarrays. Among 1750 proteins identified by proteomic analyses, keratin 4 (KRT4) and keratin 17 (KRT17) showed reciprocal patterns of expression in the spectrum of cases ranging from normal ectocervical squamous mucosa to squamous cell carcinoma. Immunohistochemical studies confirmed that KRT4 expression was significantly decreased in squamous cell carcinoma compared with the other diagnostic categories. By contrast, KRT17 expression was significantly increased in HSIL and squamous cell carcinoma compared with normal ectocervical squamous mucosa and LSIL. KRT17 was also highly expressed in immature squamous metaplasia and in endocervical reserve cells but was generally not detected in mature squamous metaplasia. Furthermore, high levels of KRT17 expression were significantly associated with poor survival of squamous cell carcinoma patients (Hazard ratio=14.76, P=0.01). In summary, both KRT4 and KRT17 expressions are related to the histopathology of the cervical squamous mucosa; KRT17 is highly overexpressed in immature squamous metaplasia, in HSIL, and in squamous cell carcinoma and the level of KRT17 in squamous cell carcinoma may help to identify patients who are at greatest risk for cervical cancer mortality.

Assessment of genomic damage and repair on human lymphocytes by paint thinner in vitro.

Paint thinners are organic-solvent complex mixtures frequently used by car painters around the world in industries and shops. Some studies have revealed the oxidative effect induced by thinner inhalation; however, its genotoxic effect is poorly studied. The aim of this study was to assess the cytotoxicity, genomic damage and DNA repair in vitro induced by commercial paint thinner 0.14 in human lymphocytes. Cytotoxicity was determined by cell-viability analysis with trypan blue after 4 h treatment with different thinner concentrations (0.025 to 1.2 µL/mL). Genomic damage was evaluated by means of the alkaline single-cell gel electrophoresis (SCGE; pH > 13) in treated cultures after 1 h with three low-cytotoxic thinner concentrations (0.05, 0.1 and 0.2 µL/mL). In order to evaluate the genomic DNA repair, one set of SCGE slides was prepared immediately after treatment, and another one was prepared after 4 h of liquid-holding recovery. A significant level of cytotoxicity was observed over the entire concentration range of paint thinner in lymphocytes (F = 175.98; p ≤ 0.001). In the SCGE % tail DNA assessment, a significant increase of lymphocyte genomic damage was evidenced (F = 72.32; p < 0.001). In addition, we found a significant decrease in the % tail DNA in thinner-treated cells after liquid-holding recovery period (all p < 0.05), demonstrating that DNA primary lesions induced by low-cytotoxic thinner concentrations are efficiently repaired. In conclusion, thinner components induce cytotoxicity and genomic damage in human lymphocytes under the study conditions, possibly by oxidative and alkylative DNA damage.

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.

Perioperative Modified FOLFIRINOX for Resectable Pancreatic Cancer: A Nonrandomized Controlled Trial.

Importance: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignant tumor, and durable disease control is rare with the current standard of care, even for patients who undergo surgical resection. Objective: To assess whether neoadjuvant modified 5-fluorouracil, leucovorin, oxaliplatin, and irinotecan (mFOLFIRINOX) leads to early control of micrometastasis and improves survival. Design, Setting, and Participants: This open-label, single-arm, phase 2 nonrandomized controlled trial for resectable PDAC was conducted at the Yale Smilow Cancer Hospital from April 3, 2014, to August 16, 2021. Pancreatic protocol computed tomography was performed at diagnosis to assess surgical candidacy. Data were analyzed from January to July 2023. Interventions: Patients received 6 cycles of neoadjuvant mFOLFIRINOX before surgery and 6 cycles of adjuvant mFOLFIRINOX. Whole blood was collected and processed to stored plasma for analysis of circulating tumor DNA (ctDNA) levels. Tumors were evaluated for treatment response and keratin 17 (K17) expression. Main Outcomes and Measures: The primary end point was 12-month progression-free survival (PFS) rate. Additional end points included overall survival (OS), ctDNA level, tumor molecular features, and K17 tumor levels. Survival curves were summarized using Kaplan-Meier estimator. Results: Of 46 patients who received mFOLFIRINOX, 31 (67%) were male, and the median (range) age was 65 (46-80) years. A total of 37 (80%) completed 6 preoperative cycles and 33 (72%) underwent surgery. A total of 27 patients (59%) underwent resection per protocol (25 with R0 disease and 2 with R1 disease); metastatic or unresectable disease was identified in 6 patients during exploration. Ten patients underwent surgery off protocol. The 12-month PFS was 67% (90% CI, 56.9-100); the median PFS and OS were 16.6 months (95% CI, 13.3-40.6) and 37.2 months (95% CI, 17.5-not reached), respectively. Baseline ctDNA levels were detected in 16 of 22 patients (73%) and in 3 of 17 (18%) after 6 cycles of mFOLFIRINOX. Those with detectable ctDNA levels 4 weeks postresection had worse PFS (hazard ratio [HR], 34.0; 95% CI, 2.6-4758.6; P = .006) and OS (HR, 11.7; 95% CI, 1.5-129.9; P = .02) compared with those with undetectable levels. Patients with high K17 expression had nonsignificantly worse PFS (HR, 2.7; 95% CI, 0.7-10.9; P = .09) and OS (HR, 3.2; 95% CI, 0.8-13.6; P = .07). Conclusions and Relevance: This nonrandomized controlled trial met its primary end point, and perioperative mFOLFIRINOX warrants further evaluation in randomized clinical trials. Postoperative ctDNA positivity was strongly associated with recurrence. K17 and ctDNA are promising biomarkers that require additional validation in future prospective studies. Trial Registration: ClinicalTrials.gov Identifier: NCT02047474.

The effect of genetic admixture in an association study: genetic polymorphisms and chromosome aberrations in a Colombian population exposed to organic solvents.

The human population is heterogeneous in genetic susceptibility, chromosomal instability and disease risk; all factors which depend on inherited genetic constitution and acquired nongenetic environmental and occupational factors. Recently, special attention has been directed to the identification of sources of potential bias in population studies of gene-environment interactions including genetic admixture. The aim of this study was to evaluate the effect of genetic admixture in the association of genetic polymorphisms and chromosome aberrations (CA) in a population exposed to organic solvents. We assessed genetic admixture via 34 genetic ancestry informative markers (AIMs) in 398 Colombian individuals. We report a statistically significant difference of higher CA frequency in individuals' below-average European component, and in individuals' above-average Native American component after adjusting for covariates. In addition, the confounding risk ratio values are ≥10% than the adjusted risk ratio, suggesting that population stratification is a confounding factor in this gene-environment association study. Furthermore, after adjusting for individual admixture proportions and covariates, the results demonstrate that glutathione-S-transferase M1 (GSTM1)-null is associated with CA frequency increase. These results suggest that gene-environment association studies that involve recently admixed populations should take into consideration population stratification as a confounding factor and suggest GSTM1-null as a genetic marker associated with CA frequency increase.

Unsupervised Stain Decomposition via Inversion Regulation for Multiplex Immunohistochemistry Images.

Multiplex Immunohistochemistry (mIHC) is a cost-effective and accessible method for in situ labeling of multiple protein biomarkers in a tissue sample. By assigning a different stain to each biomarker, it allows the visualization of different types of cells within the tumor vicinity for downstream analysis. However, to detect different types of stains in a given mIHC image is a challenging problem, especially when the number of stains is high. Previous deep-learning-based methods mostly assume full supervision; yet the annotation can be costly. In this paper, we propose a novel unsupervised stain decomposition method to detect different stains simultaneously. Our method does not require any supervision, except for color samples of different stains. A main technical challenge is that the problem is underdetermined and can have multiple solutions. To conquer this issue, we propose a novel inversion regulation technique, which eliminates most undesirable solutions. On a 7-plexed IHC images dataset, the proposed method achieves high quality stain decomposition results without human annotation.

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.

Pancreatic cancer driver mutations are targetable through distant alternative RNA splicing dependencies.

Pancreatic ductal adenocarcinoma (PDAC), the most common histological subtype of pancreatic cancer, has one of the highest case fatality rates of all known solid malignancies. Over the past decade, several landmark studies have established mutations in KRAS and TP53 as the predominant drivers of PDAC pathogenesis and therapeutic resistance, though treatment options for PDACs and other tumors with these mutations remain extremely limited. Hampered by late tumor discovery and diagnosis, clinicians are often faced with using aggressive and non-specific chemotherapies to treat advanced disease. Clinically meaningful responses to targeted therapy are often limited to the minority of patients with susceptible PDACs, and immunotherapies have routinely encountered roadblocks in effective activation of tumor-infiltrating immune cells. Alternative RNA splicing (ARS) has recently gained traction in the PDAC literature as a field from which we may better understand and treat complex mechanisms of PDAC initiation, progression, and therapeutic resistance. Here, we review PDAC pathogenesis as it relates to fundamental ARS biology, with an extension to implications for PDAC patient clinical management.

The origins and consequences of UPF1 variants in pancreatic adenosquamous carcinoma.

Pancreatic adenosquamous carcinoma (PASC) is an aggressive cancer whose mutational origins are poorly understood. An early study reported high-frequency somatic mutations affecting UPF1, a nonsense-mediated mRNA decay (NMD) factor, in PASC, but subsequent studies did not observe these lesions. The corresponding controversy about whether UPF1 mutations are important contributors to PASC has been exacerbated by a paucity of functional studies. Here, we modeled two UPF1 mutations in human and mouse cells to find no significant effects on pancreatic cancer growth, acquisition of adenosquamous features, UPF1 splicing, UPF1 protein, or NMD efficiency. We subsequently discovered that 45% of UPF1 mutations reportedly present in PASCs are identical to standing genetic variants in the human population, suggesting that they may be non-pathogenic inherited variants rather than pathogenic mutations. Our data suggest that UPF1 is not a common functional driver of PASC and motivate further attempts to understand the genetic origins of these malignancies.

Cancer is a group of complex diseases in which cells grow uncontrollably and spread into surrounding tissues and other parts of the body. All types of cancers develop from changes ­ or mutations ­ in the genes that affect the pathways involved in controlling the growth of cells. Different cancers possess unique sets of mutations that affect specific genes, and often, it is difficult to determine which of them play the most important role in a particular type of cancer. For example, pancreatic adenosquamous carcinoma, a rare and aggressive form of pancreatic cancer, is a devastating disease with a poor chance of survival ­ patients rarely live longer than one year after diagnosis. While the cells of this particular cancer display distinct features that separate them from other forms of pancreatic cancer, the genetic causes of these features are unclear. Using new technologies, some researchers have reported mutations in a 'quality control' gene called 'UPF1', which is responsible for destroying faulty forms of genetic material. However, subsequent studies did not find such mutations. To clarify the role of UPF1 in pancreatic adenosquamous carcinoma, Polaski et al. used mouse and human cancer cells with UPF1 mutations and monitored their effects on tumour growth and the development of features unique to this disease. Polaski et al. first injected mice with mouse pancreatic cancer cells containing mutations in UPF1 (mutated cells) and cancer cells without. Both groups of mice developed pancreatic tumours but there was no difference in tumour growth between the mutated and non-mutated cells, and neither cell type displayed distinct features. The researchers then generated human mutated cells, which were also found to lack any specific characteristics. Further analysis showed that the mutations did not stop UPF1 from working, in fact, over 40% of these mutations occurred naturally in humans without causing cancer. This suggests that UPF1 does not seem to be involved in pancreatic adenosquamous carcinoma. Further investigation is needed to illuminate key genetic players in the development of this type of cancer, which will be vital for improving treatments and outcomes for patients suffering from this disease.

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.

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.

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.