5 research outputs found
Expression of Checkpoint Molecules in the Tumor Microenvironment of Intrahepatic Cholangiocarcinoma: Implications for Immune Checkpoint Blockade Therapy
Background: The tumor microenvironment (TME) in cholangiocarcinoma (CCA) influences the immune environment. Checkpoint blockade is promising, but reliable biomarkers to predict response to treatment are still lacking. Materials and Methods: The levels of checkpoint molecules (PD-1, PD-L1, PD-L2, LAG-3, ICOS, TIGIT, TIM-3, CTLA-4), macrophages (CD68), and T cells (CD4 and CD8 cells) were assessed by multiplexed immunofluorescence in 50 intrahepatic cases. Associations between marker expression, immune cells, and region of expression were studied in the annotated regions of tumor, interface, sclerotic tumor, and tumor-free tissue. Results: ICCA demonstrated CD4_TIM-3 high densities in the tumor region of interest (ROI) compared to the interface (p = 0.014). CD8_PD-L1 and CD8_ICOS densities were elevated in the sclerotic tumor compared to the interface (p = 0.011 and p = 0.031, respectively). In a multivariate model, high expression of CD8_PD-L2 (p = 0.048) and CD4_ICOS_TIGIT (p = 0.011) was associated with nodal metastases. Conclusions: High densities of PD-L1 were more abundant in the sclerotic tumor region; this is meaningful for the stratification of immunotherapy. Lymph node metastasis correlates with CD4_ICOS_TIGIT co-expression and CD8_PD-L2 expression, indicating the checkpoint expression profile of patients with a poor prognosis. Also, multiple co-expressions occur, and this potentially suggests a role for combination therapy with different immune checkpoint targets than just PD-1 blockade monotherapy
The Presence of Small Nerve Fibers in the Tumor Microenvironment as Predictive Biomarker of Oncological Outcome Following Partial Hepatectomy for Intrahepatic Cholangiocarcinoma
The oncological role of the density of nerve fibers (NFs) in the tumor microenvironment (TME) in intrahepatic cholangiocarcinoma (iCCA) remains to be determined. Therefore, data of 95 iCCA patients who underwent hepatectomy between 2010 and 2019 was analyzed regarding NFs and long-term outcome. Extensive group comparisons were carried out and the association of cancer-specific survival (CSS) and recurrence-free survival (RFS) with NFs were assessed using Cox regression models. Patients with iCCA and NFs showed a median CSS of 51 months (5-year-CSS = 47%) compared to 27 months (5-year-CSS = 21%) in patients without NFs (p = 0.043 log rank). Further, NFs (hazard ratio (HR) = 0.39, p = 0.002) and N-category (HR = 2.36, p = 0.010) were identified as independent predictors of CSS. Patients with NFs and without nodal metastases displayed a mean CSS of 89 months (5-year-CSS = 62%), while patients without NFs or with nodal metastases but not both showed a median CCS of 27 months (5-year-CSS = 25%) and patients with both positive lymph nodes and without NFs showed a median CCS of 10 months (5-year-CSS = 0%, p = 0.001 log rank). NFs in the TME are, therefore, a novel and important prognostic biomarker in iCCA patients. NFs alone and in combination with nodal status is suitable to identify iCCA patients at risk of poor oncological outcomes following curative-intent surgery
Expression of Checkpoint Molecules in the Tumor Microenvironment of Intrahepatic Cholangiocarcinoma : Implications for Immune Checkpoint Blockade Therapy
Stroma and lymphocytes identified by deep learning are independent predictors for survival in pancreatic cancer
Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers known to humans. However, not all patients fare equally poor survival, and a minority of patients even survives advanced disease for months or years. Thus, there is a clinical need to search corresponding prognostic biomarkers which forecast survival on an individual basis. To dig more information and identify potential biomarkers from PDAC pathological slides, we trained a deep learning (DL) model based U-net-shaped backbone. This DL model can automatically detect tumor, stroma and lymphocytes on whole slide images (WSIs) of PDAC patients. We performed an analysis of 800 PDAC scans, categorizing stroma in percentage (SIP) and lymphocytes in percentage (LIP) into two and three categories, respectively. The presented model achieved remarkable accuracy results with a total accuracy of 94.72%, a mean intersection of union rate of 78.66%, and a mean dice coefficient of 87.74%. Survival analysis revealed that SIP-mediate and LIP-high groups correlated with enhanced median overall survival (OS) across all cohorts. These findings underscore the potential of SIP and LIP as prognostic biomarkers for PDAC and highlight the utility of DL as a tool for PDAC biomarkers detecting on WSIs
PD-1+ T-Cells Correlate with Nerve Fiber Density as a Prognostic Biomarker in Patients with Resected Perihilar Cholangiocarcinoma
SIMPLE SUMMARY: Recent studies have identified Nerve Fiber Density (NFD) as a prognostic biomarker for Cholangiocarcinoma (CCA). In the field of CCA treatment with checkpoint inhibitors (ICI) is increasing but not all patients respond. Good biomarkers to predict response to ICI are lacking. The present study investigates the immune cell composition and expression of checkpoint molecules in relation to NFD in perihilar cholangiocarcinoma (pCCA) patients. Our study identified NFD to correlate with PD-1+ T cells as a biomarker indicative for a good prognosis. ABSTRACT: Background and Aims: Perihilar cholangiocarcinoma (pCCA) is a hepatobiliary malignancy, with a dismal prognosis. Nerve fiber density (NFD)—a novel prognostic biomarker—describes the density of small nerve fibers without cancer invasion and is categorized into high numbers and low numbers of small nerve fibers (high vs low NFD). NFD is different than perineural invasion (PNI), defined as nerve fiber trunks invaded by cancer cells. Here, we aim to explore differences in immune cell populations and survival between high and low NFD patients. Approach and Results: We applied multiplex immunofluorescence (mIF) on 47 pCCA patients and investigated immune cell composition in the tumor microenvironment (TME) of high and low NFD. Group comparison and oncological outcome analysis was performed. CD8+PD-1 expression was higher in the high NFD than in the low NFD group (12.24 × 10(−6) vs. 1.38 × 10(−6) positive cells by overall cell count, p = 0.017). High CD8+PD-1 expression was further identified as an independent predictor of overall (OS; Hazard ratio (HR) = 0.41; p = 0.031) and recurrence-free survival (RFS; HR = 0.40; p = 0.039). Correspondingly, the median OS was 83 months (95% confidence interval (CI): 18–48) in patients with high CD8+PD-1+ expression compared to 19 months (95% CI: 5–93) in patients with low CD8+PD-1+ expression (p = 0.018 log rank). Furthermore, RFS was significantly lower in patients with low CD8+PD-1+ expression (14 months (95% CI: 6–22)) compared to patients with high CD8+PD-1+ expression (83 months (95% CI: 17–149), p = 0.018 log rank). Conclusions: PD-1+ T-cells correlate with high NFD as a prognostic biomarker and predict good survival; the biological pathway needs to be investigated
