Ali Akalin’s research while affiliated with University of Massachusetts Chan Medical School and other places

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.

Inhalation of airborne conidia of the ubiquitous fungus Aspergillus fumigatus commonly occurs but invasive aspergillosis is rare except in profoundly immunocompromised persons. Severe influenza predisposes patients to invasive pulmonary aspergillosis by mechanisms that are poorly defined. Using a post-influenza aspergillosis model, we found that superinfected mice had 100% mortality when challenged with A. fumigatus conidia on days 2 and 5 (early stages) of influenza A virus infection but 100% survival when challenged on days 8 and 14 (late stages). Influenza-infected mice superinfected with A. fumigatus had increased levels of the pro-inflammatory cytokines and chemokines interleukin (IL)-6, tumor necrosis factor (TNF)α, interferon (IFN)β, IL-12p70, IL-1α, IL-1β, CXC motif chemokine ligand 1 (CXCL1), granulocyte-colony-stimulating factor (G-CSF), macrophage inflammatory protein (MIP)-1α, MIP-1β, regulated upon activation, normal T cell expressed and presumably secreted (RANTES), and monocyte chemoattractant protein (MCP)-1. Surprisingly, on histopathological analysis, superinfected mice did not have greater lung inflammation compared with mice infected with influenza alone. Mice infected with influenza had dampened neutrophil recruitment to the lungs following subsequent challenge with A. fumigatus, but only if the fungal challenge was executed during the early stages of influenza infection. However, influenza infection did not have a major effect on neutrophil phagocytosis and killing of A. fumigatus conidia. Moreover, minimal germination of conidia was seen on histopathology even in the superinfected mice. Taken together, our data suggest that the high mortality rate seen in mice during the early stages of influenza-associated pulmonary aspergillosis is multifactorial with a greater contribution from dysregulated inflammation than microbial growth. IMPORTANCE Severe influenza is a risk factor for fatal invasive pulmonary aspergillosis; however, the mechanistic basis for the lethality is unclear. Utilizing an influenza-associated pulmonary aspergillosis (IAPA) model, we found that mice infected with influenza A virus followed by Aspergillus fumigatus had 100% mortality when superinfected during the early stages of influenza but survived at later stages. While superinfected mice had dysregulated pulmonary inflammatory responses compared to controls, they had neither increased inflammation nor extensive fungal growth. Although influenza-infected mice had dampened neutrophil recruitment to the lungs following subsequent challenge with A. fumigatus, influenza did not affect the ability of neutrophils to clear the fungi. Our data suggest that the lethality seen in our model of IAPA is multifactorial with dysregulated inflammation being a greater contributor than uncontrollable microbial growth. If confirmed in humans, our findings provide a rationale for clinical studies of adjuvant anti-inflammatory agents in the treatment of IAPA.

Inhalation of airborne conidia of the ubiquitous fungus Aspergillus fumigatus commonly occurs but invasive aspergillosis is rare except in profoundly immunocompromised persons. Severe influenza predisposes patients to invasive pulmonary aspergillosis by mechanisms that are poorly defined. Using a post-influenza aspergillosis model, we found that superinfected mice had 100% mortality when challenged with A. fumigatus conidia on days 2 and 5 (early stages) of influenza A virus infection but 100% survival when challenged on days 8 and 14 (late stages). Influenza-infected mice superinfected with A. fumigatus had increased levels of the pro-inflammatory cytokines and chemokines IL-6, TNFα, IFNβ, IL-12p70, IL-1α, IL-1β, CXCL1, G-CSF, MIP-1α, MIP-1β, RANTES and MCP-1. Surprisingly, on histopathological analysis, superinfected mice did not have greater lung inflammation compared with mice infected with influenza alone. Mice infected with influenza had dampened neutrophil recruitment to the lungs following subsequent challenge with A. fumigatus , but only if the fungal challenge was executed during the early stages of influenza infection. However, influenza infection did not have a major effect on neutrophil phagocytosis and killing of A. fumigatus conidia. Moreover, minimal germination of conidia was seen on histopathology even in the superinfected mice. Taken together, our data suggest that the high mortality rate seen in mice during the early stages of influenza-associated pulmonary aspergillosis is multifactorial, with a greater contribution from dysregulated inflammation than microbial growth. Importance Severe influenza is a risk factor for fatal invasive pulmonary aspergillosis; however, the mechanistic basis for the lethality is unclear. Utilizing an influenza-associated pulmonary aspergillosis (IAPA) model, we found that mice infected with influenza A virus followed by A. fumigatus had 100% mortality when superinfected during the early stages of influenza but survived at later stages. While superinfected mice had dysregulated pulmonary inflammatory responses compared to controls, they had neither increased inflammation nor extensive fungal growth. Although influenza-infected mice had dampened neutrophil recruitment to the lungs following subsequent challenge with A. fumigatus , influenza did not affect the ability of neutrophils to clear the fungi. Our data suggest that the lethality seen in our model IAPA is multifactorial with dysregulated inflammation being a greater contributor than uncontrollable microbial growth. If confirmed in humans, our findings provide a rationale for clinical studies of adjuvant anti-inflammatory agents in the treatment of IAPA.

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 the assessment of these patients. Prior studies have established that keratin 17 (K17) is a negative prognostic biomarker in a wide range of cancer types, including pulmonary adenocarcinoma (LUAD). Although keratin expression profiles have been widely utilized as markers to distinguish between metastatic versus primary squamous cell carcinomas (SCC), K17 has not been previously investigated for its potential accuracy as a prognostic biomarker in lung squamous cell carcinoma (LSCC). Here, we set out to determine if K17 is a prognostic biomarker that drives poor survival in both LSCC and LUAD. Data mining was performed to analyze K17 mRNA in independent cohorts of LSCC (n=266) and LUAD (n=271) and immunohistochemistry (IHC) for K17 was performed in separate cohorts of LSCC (n=84) and LUAD (n=107). Kaplan-Meier and Cox proportional-hazard regression models were used to determine overall survival differences between low vs. high K17 expressing cases. High K17 mRNA correlated with decreased overall survival in both LSCC (HR: 1.789, p=0.0646) and LUAD (HR: 1.894, p=0.0142). Similarly, by IHC, high K17 correlated with decreased overall survival in LSCC (HR: 1.894, p=0.0375) and LUAD (HR: 2.105, p=0.0257). Thus, K17, defined either by mRNA expression or immunohistochemical staining, is a negative prognostic biomarker for non-small cell lung cancer.

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 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 (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.

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.