Response In Pancreatic Adenocarcinoma Research Articles

A five-gene prognosis model based on lysine β-hydroxybutyrylation site genes to predict the survival and therapy response in pancreatic adenocarcinoma

BackgroundPancreatic adenocarcinoma (PAAD) is one of the most malignancy diseases. Lysine β-hydroxybutyrylation (Kbhb) has been reported to involve various metabolism and cancer progression. MethodsData from online databases (TCGA and GEO) were retrieved for the selection of differential expressed Kbhb site genes (DTRGs). Univariate cox and LASSO analysis were performed to identified the prognostic DTRGs. Based on the optimal DTRGs, a prognostic risk score model was established. Kaplan-Meier and Receiver operator characteristic analysis were conducted to evaluate the predicting ability of the prognosis model. Generated with clinical data, independent analysis and nomogram model were performed. Finally, the difference of survival, immune cell levels, immunotherapy response, drug sensitivity between high- and low-risk groups were explored. ResultsA total of 63 DTRGs were identified in PAAD, and these genes were related to cell division and apoptosis biological functions. Through univariate cox regression and LASSO analysis, 30 DTRGs were selected to be related to prognosis and five (KRT18, ANLN, ECT2, RBM5, and RBM6) were identified as the optimal DTRGs in PAAD. Based on the five optimal DTRGs, a prognostic risk score model was constructed, with promising predictive ability in PAAD survival (AUC > 0.70). High-risk group showed lower survival rate (P < 0.05). Moreover, based on the risk score, a nomogram model was also established, which possessed perfect stability. Finally, lower risk score was related to higher immune cell levels, indicating an immune activation in low-risk status, which maybe the reason for the better survival in low-risk group. Furthermore, the immunotherapy response and drug sensitivity were all higher than that in low-risk groups (P < 0.05). ConclusionA five-gene prognosis risk model which exhibit promising predictive ability in survival is constructed for patients with PAAD.

A five-gene prognosis model based on lysine β-hydroxybutyrylation site genes to predict the survival and therapy response in pancreatic adenocarcinoma

BackgroundPancreatic adenocarcinoma (PAAD) is one of the most malignancy diseases. Lysine β-hydroxybutyrylation (Kbhb) has been reported to involve various metabolism and cancer progression. MethodsData from online databases (TCGA and GEO) were retrieved for the selection of differential expressed Kbhb site genes (DTRGs). Univariate cox and LASSO analysis were performed to identified the prognostic DTRGs. Based on the optimal DTRGs, a prognostic risk score model was established. Kaplan-Meier and Receiver operator characteristic analysis were conducted to evaluate the predicting ability of the prognosis model. Generated with clinical data, independent analysis and nomogram model were performed. Finally, the difference of survival, immune cell levels, immunotherapy response, drug sensitivity between high- and low-risk groups were explored. ResultsA total of 63 DTRGs were identified in PAAD, and these genes were related to cell division and apoptosis biological functions. Through univariate cox regression and LASSO analysis, 30 DTRGs were selected to be related to prognosis and five (KRT18, ANLN, ECT2, RBM5, and RBM6) were identified as the optimal DTRGs in PAAD. Based on the five optimal DTRGs, a prognostic risk score model was constructed, with promising predictive ability in PAAD survival (AUC > 0.70). High-risk group showed lower survival rate (P < 0.05). Moreover, based on the risk score, a nomogram model was also established, which possessed perfect stability. Finally, lower risk score was related to higher immune cell levels, indicating an immune activation in low-risk status, which maybe the reason for the better survival in low-risk group. Furthermore, the immunotherapy response and drug sensitivity were all higher than that in low-risk groups (P < 0.05). ConclusionA five-gene prognosis risk model which exhibit promising predictive ability in survival is constructed for patients with PAAD.

CHST12: a potential prognostic biomarker related to the immunotherapy response in pancreatic adenocarcinoma.

Pancreatic adenocarcinoma (PAAD) is characterized by lower immunogenicity with a poor response rate to immune checkpoint inhibitors (ICIs) and exhibits the poorest prognosis of all solid tumors, which results in the highest tumor-related mortality among malignancies. However, the underlying mechanisms are poorly understood. In addition, diverse carbohydrate sulfotransferases (CHSTs), which are involved in the sulfation process of these structures, play an important role in the metastatic spread of tumor cells. Aberrant glycosylation is beginning to emerge as an influencing factor in tumor immunity and immunotherapy. Therefore, it might serve as a biomarker of the immunotherapeutic response in tumors. The purpose of the study was to evaluate the role of CHST12 in PAAD prognosis and its relevance to the immunotherapeutic response. A comprehensive investigation of the interactions between CHST12 expression and the immune microenvironment as well as the clinical significance of CHST12 in PAAD was conducted. Data derived from the Cancer Genome Atlas (TCGA) database were analyzed using univariate and multivariate approaches, the Tumor Immune Estimation Resource (TIMER), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. Publicly available datasets were analyzed in this study. These data can be found on websites such as http://www.xiantao.love and https://www.proteinatlas.org. An assessment of the predictive value of CHST12 for PAAD prognosis was conducted using univariate and multivariate Cox regression analysis, Kaplan-Meier analysis, and nomograms. The TIMER algorithm calculates the proportions of six types of immune cells. The TIDE algorithm was used to indicate the characteristics of tumors that respond to ICI therapy. The mRNA and protein levels of CHST12 showed the opposite trend. CHST12 mRNA expression was significantly upregulated in PAAD. According to Cox regression analysis, CHST12 RNA expression acts as a protective factor for overall survival [hazard ratio (HR), 0.617, P < 0.04]. Functional annotation indicated that CHST12-associated differentially expressed genes (DEGs) were related to the signaling activity of receptor tyrosine kinases and the regulation of ubiquitin-protein transferase. These are usually involved in tumor development and may be related to the treatment responses of immune checkpoint inhibitors (ICIs). There was significantly higher CHST12 mRNA expression in PAAD samples than in non-malignant samples. In PAAD, elevated CHST12 mRNA expression might regulate immune cell infiltration into the tumor microenvironment (TME) and may predict clinical outcomes.

A novel sphingolipid metabolism-related long noncoding RNA signature predicts the prognosis, immune landscape and therapeutic response in pancreatic adenocarcinoma

Sphingolipid metabolism affects prognosis and resistance to immunotherapy in patients with cancer and is an emerging target in cancer therapy with promising diagnostic and prognostic value. Long noncoding ribonucleic acids (lncRNAs) broadly regulate tumour-associated metabolic reprogramming. However, the potential of sphingolipid metabolism-related lncRNAs in pancreatic adenocarcinoma (PAAD) is poorly understood. In this study, coexpression algorithms were employed to identify sphingolipid metabolism-related lncRNAs. The least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a sphingolipid metabolism-related lncRNA signature (SMLs). The prognostic predictive stability of the SMLs was validated using Kaplan–Meier. Univariate and multivariate Cox, receiver operating characteristic (ROC) and clinical stratification analyses were used to comprehensively assess the SMLs. Gene set variation analysis (GSVE), gene ontology (GO) and tumor mutation burden (TMB) analysis explored the potential mechanisms. Additionally, single sample gene set enrichment analysis (ssGSEA), ESTIMATE, immune checkpoints and drug sensitivity analysis were used to investigate the potential predictive function of the SMLs. Finally, an SMLs-based consensus clustering algorithm was utilized to differentiate patients and determine the suitable population for immunotherapy. The results showed that the SMLs consists of seven sphingolipid metabolism-related lncRNAs, which can well determine the clinical outcome of individuals with PAAD, with high stability and general applicability. In addition, the SMLs-based consensus clustering algorithm divided the TCGA-PAAD cohort into two clusters, with Cluster 1 showing better survival than Cluster 2. Additionally, Cluster 1 had a higher level of immune cell infiltration than Cluster 2, which combined with the higher levels of immune checkpoints in Cluster 1 suggests that Cluster 1 is more consistent with an immune ‘hot tumor’ profile and may respond better to immune checkpoint inhibitors (ICIs). This study offers new insights regarding the potential role of sphingolipid metabolism-related lncRNAs as biomarkers in PAAD. The constructed SMLs and the SMLs-based clustering are valuable tools for predicting clinical outcomes in PAAD and provide a basis for clinical selection of individualized treatments.

Prognostic Value and the Immune Microenvironment-associated Role of SMAD4 in Pancreatic Adenocarcinoma.

SMAD4 is a well-known cancer suppressor gene that regulates cell proliferation, differentiation, autoimmunity, pluripotency, and immune responses in pancreatic adenocarcinoma (PAAD). We herein investigated a novel involvement of SMAD4 within the PAAD microenvironment. Transcriptome data, derived from The Cancer Genome Atlas and Genotype-Tissue Expression Using TIMER 2.0, CIBERSORT, and ImmuCellAI, were used to identify the immune cell infiltration pattern of PAAD. We then knocked-down SMAD4 in the PANC-1 cell line and acquired RNA-seq data through the Illumina microarray technology. Kyoto Encyclopedia of Genes and Genomes was utilized along with Gene Ontology enrichment analyses, and protein-protein interaction network analysis to screen for genes that were differentially expressed. We constructed a miRNA-mRNA regulatory network and analyzed SMAD4 copy number variation (CNV) data. In PAAD, decreased levels of SMAD4 expression were found to be connected to an unfavorable prognosis. There was a significantly higher infiltration level of DC cells, CD8+ T cells, TgD, Tc, and Tex cells and a lower level of B cells and Th2 in the SMAD4-high group. The expression of SMAD4 and immune cell infiltration including CD8+ T cells, myeloid dendritic cells, neutrophils, and macrophages are significantly positively correlated. DEGs were found enriched in the hypoxia response pathway. The six hypoxia-related genes exhibited a significant correlation with immune cell infiltration and survival rates. SMAD4 CNV levels were associated with MSI, stemness, infiltration of immune cells, and survival rates. A statistically significant correlation was found between SMAD4 expression and immune cell infiltration. SMAD4 could mediate hypoxia response in pancreatic cancer. The CNV levels of SMAD4 were associated with prognosis. SMAD4 has potential as a prognostic biomarker and provides a new orientation for the immunotherapy of PAAD.

Cancer-associated fibroblast-related prognostic signature predicts prognosis and immunotherapy response in pancreatic adenocarcinoma based on single-cell and bulk RNA-sequencing

Cancer-associated fibroblasts (CAFs) influence many aspects of pancreatic adenocarcinoma (PAAD) carcinogenesis, including tumor cell proliferation, angiogenesis, invasion, and metastasis. A six-gene prognostic signature was constructed for PAAD based on the 189 CAF marker genes identified in single-cell RNA-sequencing data. Multivariate analyses showed that the risk score was independently prognostic for survival in the TCGA (P < 0.001) and ICGC (P = 0.004) cohorts. Tumor infiltration of CD8 T (P = 0.005) cells and naïve B cells (P = 0.001) was greater in the low-risk than in the high-risk group, with infiltration of these cells negatively correlated with risk score. Moreover, the TMB score was lower in the low-risk than in the high-risk group (P = 0.0051). Importantly, patients in low-risk group had better immunotherapy responses than in the high-risk group in an independent immunotherapy cohort (IMvigor210) (P = 0.039). The CAV1 and SOD3 were highly expressed in CAFs of PAAD tissues, which revealed by immunohistochemical staining. In summary, this comprehensive analysis resulted in the development of a novel prognostic signature, which was associated with immune cell infiltration, drug sensitivity, and TMB, and could predict the prognosis and immunotherapy response of patients with PAAD.

Construction of an efferocytosis-related long non-coding ribonucleic acid scoring system to predict clinical outcome and immunotherapy response in pancreatic adenocarcinoma

BackgroundEfferocytosis suppresses antitumour immune responses by inducing the release and secretion of cytokines. Long non-coding ribonucleic acids (lncRNAs) have various functions in different forms of programmed cell death and in immune regulation. This study aims to explore the potential role of efferocytosis-related lncRNAs as biomarkers in pancreatic adenocarcinoma (PAAD). MethodsTranscriptome profiles, simple nucleotide variations and clinical data of patients with PAAD were extracted from The Cancer Genome Atlas (TCGA) database. Co-expression algorithms identified efferocytosis-related lncRNAs. The efferocytosis-related lncRNA scoring system (ERLncSys) was established using Cox regression and the Least Absolute Shrinkage and Selection Operator algorithm. Additionally, Kaplan-Meier (K-M) curves, Cox regression, receiver operating characteristic (ROC) curves and clinical parameter stratification analyses were used to evaluate ERlncSys. Moreover, ERlncSys was explored through Gene Set Variation Analysis, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Furthermore, the TIMER platform, ESTIMATE algorithm, single sample Gene Set Enrichment Analysis and immune checkpoint analysis were utilised to explore the predictive power of ERlncSys for the tumour immune microenvironment (TIME). Finally, a consensus clustering algorithm identified distinct molecular profiles among patients with PAAD, aiding in the identification of potential beneficiaries for immunotherapy. ResultsK-M, Cox regression and ROC analyses confirmed the robust prognostic efficacy of ERlncSys. Clinical stratification analysis indicated the broad applicability of ERlncSys in PAAD. Additionally, mmunological analyses indicated that ERlncSys can determine immune cell infiltration status in the TIME. Furthermore, consensus clustering analysis based on ERlncSys divided the TCGA-PAAD cohort into two clusters. Cluster 1 exhibited characteristics consistent with an immune ‘hot tumour’ compared to cluster 2, suggesting cluster 1 is a more suitable population for immune checkpoint inhibitor therapy. ConclusionThe established ErlncSys aids in predicting the prognosis and understanding the TIME landscape of patients with PAAD. In turn, it facilitates the identification of optimal candidates for immunotherapy. This study introduces novel insights into the potential value of efferocytosis-related lncRNAs as biomarkers in PAAD.

From bugs to drugs: Bacterial 3-IAA enhances efficacy of chemotherapy in pancreatic cancer

Tintelnot etal.1 identified enrichment of indole-3-acetic acid (3-IAA), a tryptophan metabolite produced by gut microbiota, as a predictor of chemotherapy response in pancreatic adenocarcinoma. Recapitulated in mouse models, 3-IAA represents a novel potential therapeutic approach for chemotherapy sensitization.

A novel cuproptosis-related gene model predicts outcomes and treatment responses in pancreatic adenocarcinoma

BackgroundCuproptosis is recently emerging as a hot spot in cancer research. However, its role in pancreatic adenocarcinoma (PAAD) has not yet been clarified. This study aimed to explore the prognostic and therapeutic implications of cuproptosis-related genes in PAAD.MethodsTwo hundred thirteen PAAD samples from the International Cancer Genome Consortium (ICGC) were split into training and validation sets in the ratio of 7:3. The Cox regression analyses generated a prognostic model using the ICGC cohort for training (n = 152) and validation (n = 61). The model was externally tested on the Gene Expression Omnibus (GEO) (n = 80) and The Cancer Genome Atlas (TCGA) datasets (n = 176). The clinical characteristics, molecular mechanisms, immune landscape, and treatment responses in model-defined subgroups were explored. The expression of an independent prognostic gene TSC22D2 was confirmed by public databases, real-time quantitative PCR (RT-qPCR), western blot (WB), and immunohistochemistry (IHC).ResultsA prognostic model was established based on three cuproptosis-related genes (TSC22D2, C6orf136, PRKDC). Patients were stratified into high- and low-risk groups using the risk score based on this model. PAAD patients in the high-risk group had a worse prognosis. The risk score was statistically significantly correlated with most clinicopathological characteristics. The risk score based on this model was an independent predictor of overall survival (OS) (HR = 10.7, p < 0.001), and was utilized to create a scoring nomogram with excellent prognostic value. High-risk patients had a higher TP53 mutation rate and a superior response to multiple targeted therapies and chemotherapeutic drugs, but might obtain fewer benefits from immunotherapy. Moreover, elevated TSC22D2 expression was discovered to be an independent prognostic predictor for OS (p < 0.001). Data from public databases and our own experiments showed that TSC22D2 expression was significantly higher in pancreatic cancer tissues/cells compared to normal tissues/cells.ConclusionThis novel model based on cuproptosis-related genes provided a robust biomarker for predicting the prognosis and treatment responses of PAAD. The potential roles and underlying mechanisms of TSC22D2 in PAAD need further explored.

Characterization of Estrogen Receptors in Pancreatic Adenocarcinoma with Tertiary Lymphoid Structures.

The role of estrogen signaling in antitumor immunology remains unknown for non-traditional sex-biased cancer types such as pancreatic adenocarcinoma (PAAD). Tertiary lymphoid structures (TLS) are active zones composed of multiple types of immune cells, whose presence indicates anti-tumor immune responses. In this study, we employed a 12-chemokine signature to characterize potential gene categories associated with TLS development and identified seventeen major gene categories including estrogen receptors (ERs). Immunohistochemistry staining revealed the expression patterns of three ERs (ERα, ERβ, and GPER) in 174 PAAD samples, and their correlation with clinicopathological characteristics, immune cell infiltration levels, and intratumoral TLS presence was analyzed. The results indicated that ERα (+) and ERβ (+) were correlated with high tumor grade, and ERβ (+) and GPER (+) were correlated with lower TNM stage, and both ERα (+) and GPER (+) displayed a beneficial effect on prognosis in this cohort. Interestingly, positive staining of all three ERs was significantly correlated with the presence of intratumoral TLSs and infiltration of more active immune cells into the microenvironment. Moreover, the chemotaxis of CD8+T-cells to PAAD cells was significantly increased in vitro with upregulated expression of ERα or ERβ on PAAD cells. To conclude, our study showed a novel correlation between ER expression and TLS development, suggesting that ERs may play a protective role by enhancing anti-tumor immune responses in PAAD.

Determination of a DNA repair-related gene signature with potential implications for prognosis and therapeutic response in pancreatic adenocarcinoma.

Pancreatic adenocarcinoma (PAAD) is one of the leading causes of cancer death worldwide. Alterations in DNA repair-related genes (DRGs) are observed in a variety of cancers and have been shown to affect the development and treatment of cancers. The aim of this study was to develop a DRG-related signature for predicting prognosis and therapeutic response in PAAD. We constructed a DRG signature using least absolute shrinkage and selection operator (LASSO) Cox regression analysis in the TCGA training set. GEO datasets were used as the validation set. A predictive nomogram was constructed based on multivariate Cox regression. Calibration curve and decision curve analysis (DCA) were applied to validate the performance of the nomogram. The CIBERSORT and ssGSEA algorithms were utilized to explore the relationship between the prognostic signature and immune cell infiltration. The pRRophetic algorithm was used to estimate sensitivity to chemotherapeutic agents. The CellMiner database and PAAD cell lines were used to investigate the relationship between DRG expression and therapeutic response. We developed a DRG signature consisting of three DRGs (RECQL, POLQ, and RAD17) that can predict prognosis in PAAD patients. A prognostic nomogram combining the risk score and clinical factors was developed for prognostic prediction. The DCA curve and the calibration curve demonstrated that the nomogram has a higher net benefit than the risk score and TNM staging system. Immune infiltration analysis demonstrated that the risk score was positively correlated with the proportions of activated NK cells and monocytes. Drug sensitivity analysis indicated that the signature has potential predictive value for chemotherapy. Analyses utilizing the CellMiner database showed that RAD17 expression is correlated with oxaliplatin. The dynamic changes in three DRGs in response to oxaliplatin were examined by RT-qPCR, and the results show that RAD17 is upregulated in response to oxaliplatin in PAAD cell lines. We constructed and validated a novel DRG signature for prediction of the prognosis and drug sensitivity of patients with PAAD. Our study provides a theoretical basis for further unraveling the molecular pathogenesis of PAAD and helps clinicians tailor systemic therapies within the framework of individualized treatment.

LDHA is a prognostic biomarker on the immune response in pancreatic adenocarcinoma and associated with m6A modification.

N6-methyladenosine (m6A) is tightly associated with the progression of pancreatic ductal adenocarcinoma (PDAC). Another prominent feature of PDAC is metabolic reprogramming, which provides sufficient nutrients to support rapid cell growth via the tumor microenvironment. However, the underlying influences of m6A-associated metabolic genes on the PDAC microenvironment remain poorly understood. Therefore, we sought to construct a survival prediction model using m6A-related genes to clarify the molecular characteristics of PDAC. In the present study, m6A-related metabolic genes were obtained from The Cancer Genome Atlas (TCGA) pancreatic adenocarcinoma dataset and subjected to coexpression analysis. Consensus clustering recognized two distinct subgroups with different immune cell infiltration patterns according to the expression of m6A-associated metabolic genes. Multivariate Cox regression analyses and least absolute shrinkage and selection operator (LASSO) analysis were adopted to create an m6A-related metabolism model. A nomogram including clinical features and the risk score based on the expression of m6A-related metabolism regulators was constructed. A four-gene signature comprising ATP8B2, GMPS, LDHA and SDR39U1 was built to predict the overall survival (OS) of PDAC patients. This signature also robustly predicted survival in two independent validation cohorts from the International Cancer Genome Consortium (ICGC) and ArrayExpress (E-MTAB-6134). The four-gene signature divided patients into high- and low-risk groups with distinct OS values as verified by the log-rank test. Among the four genes, LDHA was upregulated in both PDAC tissues and cell lines. Collectively, we analyzed the immune microenvironment, predicted drug sensitivity and assessed the implications of the mutation landscape based on the crosstalk between m6A regulators and metabolic rewiring, and we also constructed a novel signature based on m6A-associated metabolic genes to predict PDAC prognosis.

Cuproptosis scoring model predicts overall survival and assists in immunotherapeutic decision making in pancreatic carcinoma.

Background: Cuproptosis is a newly identified form of non-apoptotic cell death that is associated with the progression and treatment responses in pancreatic adenocarcinoma (PAAD). However, its impact on oncology and tumor microenvironment (TME) remains unclear. Methods: Hub genes were identified using least absolute shrinkage and selection operator (LASSO) Cox regression for 25 newly reported cuproptosis-related regulators and subjected to stepwise regression to obtain cuproptosis-related score (CuRS). Additionally, the clinical significance, functional status, role on TME, and genomic variation of CuRS were further examined systematically. Results: A CuRS model incorporating TRAF2, TRADD, USP21, FAS, MLKL, TNFRSF10B, MAPK8, TRAF5, and RIPK3 was developed. The stability and accuracy of this risk model as an independent prognostic factor for PAAD were confirmed in the training and external validation cohorts. Patients in the high-CuRS group had “cold” tumors with active tumor proliferation and immunosuppression, whereas those in the low-CuRS group comprised “hot” tumors with active immune function and cell killing capacity. Additionally, patients in the high-CuRS group carried fewer genomic copy number variations (CNVs) and greater somatic mutations. Furthermore, patients in the low- and high-CuRS groups exhibited increased sensitivity to immunotherapy and chemotherapy, respectively. Conclusion: We developed and validated a robust CuRS model based on cuproptosis to assess patients’ prognoses and guide clinical decision-making. Overall, the findings of this study are expected to contribute to the comprehensive understanding of cuproptosis and facilitate precise treatment of PAAD.

Abstract LB116: CXCL8/Interleukin-8 orchestrates radiation-induced immune responses in pancreatic adenocarcinoma

Abstract The role of radiotherapy in the treatment of pancreatic adenocarcinoma (PDAC) is controversial. In many other tumor types, radiotherapy is a mainstay therapy whose anti-tumor effects have partially been ascribed to T cell responses. The role of Natural Killer (NK) cells in radiotherapy tumor responses remains unclear. Here, we focused on the role of NK cells in radiotherapy of pancreatic cancer. In a randomized controlled pancreatic cancer trial, we found that CXCL8 serum levels increased under radiotherapy and NK cells positively correlated with prolonged overall patient survival. Accordingly, NK cells preferentially infiltrated irradiated tumors and exhibited CD56dim like cytotoxic transcriptomic states. In preclinical experimental systems in mice and tumor cells, NF-κB and mTOR signaling prompted radiation-induced CXCL8 secretion from senescent tumor cells causing directional migration of CD56dim NK cells into tumors. Thus, we link senescence-associated CXCL8 release to innate immune surveillance of human tumors. Moreover, combined radiotherapy and adoptive NK cell transfer improved tumor control over monotherapies in xenografted mice suggesting NK cells combined with radiotherapy as a rational cancer treatment strategy which may be integrated into PDAC treatment algorithms. Citation Format: Thomas Walle, Joscha A. Kraske, Boyu Liao, Carmen Timke, Benedicte Lenoir, Niels Halama, Peter E. Huber. CXCL8/Interleukin-8 orchestrates radiation-induced immune responses in pancreatic adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB116.

High tumor mutational burden (TMB) identifies a microsatellite stable pancreatic cancer subset with prolonged survival and strong anti-tumor immunity

AimTumor mutational burden (TMB: somatic mutations per megabase, mut/Mb) predicts the efficacy of immunotherapy. Here, we link TMB levels with the activation of immune pathways and intratumoral immune responses in pancreatic adenocarcinoma (PDAC) to explore immunoarchitectural patterns associated with high TMB. MethodsWe assessed TMB in 161 resected, microsatellite stable (MSS) PDACs, including 41 long-term survivors (LTS). Five microsatellite instable (MSI-high) cases were also assessed. Cases were classified into TMB-high (≥10 mut/Mb), TMB-intermediate (>5 < 10 mut/Mb), and TMB-low (≤5 mut/Mb) categories. Tumors additionally underwent mRNA in situ hybridization for immune pathway genes and were immunoprofiled by multiplex immunofluorescence followed by automated image analysis. ResultsWe detected 12 TMB-high, 28 TMB-intermediate, and 121 TMB-low cases. TMB-high tumors comprised ten LTSs (10/41; 24%) and two conventional PDACs (2/120; 1.7%). They exhibited the highest T cell density with significantly increased CD3+CD4+T helper and CD208+dendritic cell (DC) counts, compared to all other cases. CD3+CD8+cytotoxic T cells were significantly closer to tumor cells and T helper cells closer to DCs in TMB-high PDACs. Immune pathways involved in T cell activation, immune cell adhesion/migration, antigen presentation, and cytokine signaling were upregulated in most TMB-high and many TMB-intermediate tumors. ARID1A and ERBB4 alterations were more frequent in TMB-high PDACs. All MSI-high PDACs were TMB-high. ConclusionsTMB-high cases frequently belong to specific PDAC subsets with prolonged survival such as LTSs and MSI-high PDACs. They display strong anti-tumor immune responses fueled by a T helper cell/DC-mediated priming of the cytotoxic T cells. Moreover, they frequently harbor further actionable alterations.

Total neoadjuvant therapy is associated with improved overall survival and pathologic response in pancreatic adenocarcinoma.

Few studies have evaluated outcomes of total neoadjuvant therapy (TNT) compared with single modality neoadjuvant therapy (SMNT) or surgery first (SF) for pancreatic ductal adenocarcinoma (PDAC). A single-institution retrospective review of PDAC patients who underwent pancreatectomy was conducted (1993-2019). Overall survival (OS) estimates from diagnosis and from surgery were determined using Kaplan-Meier methods; Cox proportional hazards models adjusted for covariates. Surgery was performed upfront (SF) in 168 (46.9%), while 111 (31.0%) had chemotherapy or chemoradiation before resection (SMNT), and 79 (22.1%) underwent TNT (chemotherapy and chemoradiation). Resection margins were more frequently R0 in the TNT group (86.1%) compared with SMNT (64.0%) and SF (72%) (p < 0.001). Complete pathologic response was more common in the TNT group (10.1%) compared with SMNT (3.6%) or SF (0.6%) (p = 0.001), resulting in prolonged survival (median OS = 100.2 months). TNT patients demonstrated longer median OS from surgery (33.6 months) compared with SF (19.1 months) and SMNT (17.4 months) (p = 0.010), which persisted after controlling for covariates. TNT is associated with more frequent complete pathologic response, a higher rate of margin negative resection, and prolonged OS as compared with SF or SMNT. Additional studies to identify subgroups that derive the greatest benefit are warranted.

Targeting Treg-Expressed STAT3 Enhances NK-Mediated Surveillance of Metastasis and Improves Therapeutic Response in Pancreatic Adenocarcinoma.

Metastasis remains a major hurdle in treating aggressive malignancies such as pancreatic ductal adenocarcinoma (PDAC). Improving response to treatment, therefore, requires a more detailed characterization of the cellular populations involved in controlling metastatic burden. PDAC patient tissue samples were subjected to RNA sequencing analysis to identify changes in immune infiltration following radiotherapy. Genetically engineered mouse strains in combination with orthotopic tumor models of PDAC were used to characterize disease progression. Flow cytometry was used to analyze tumor infiltrating, circulating, and nodal immune populations. We demonstrate that although radiotherapy increases the infiltration and activation of dendritic cells (DC), it also increases the infiltration of regulatory T cells (Treg) while failing to recruit natural killer (NK) and CD8 T cells in PDAC patient tissue samples. In murine orthotopic tumor models, we show that genetic and pharmacologic depletion of Tregs and NK cells enhances and attenuates response to radiotherapy, respectively. We further demonstrate that targeted inhibition of STAT3 on Tregs results in improved control of local and distant disease progression and enhanced NK-mediated immunosurveillance of metastasis. Moreover, combination treatment of STAT3 antisense oligonucleotide (ASO) and radiotherapy invigorated systemic immune activation and conferred a survival advantage in orthotopic and metastatic tumor models. Finally, we show the response to STAT3 ASO + radiotherapy treatment is dependent on NK and DC subsets. Our results suggest targeting Treg-mediated immunosuppression is a critical step in mediating a response to treatment, and identifying NK cells as not only a prognostic marker of improved survival, but also as an effector population that functions to combat metastasis.

Mutations in lysine methyltransferase 2C and PEG3 are associated with tumor mutation burden, prognosis, and antitumor immunity in pancreatic adenocarcinoma patients.

BackgroundAs a common cancer-related death worldwide, pancreatic adenocarcinoma (PAAD) has significantly increased mortality in recent years. In recent years, tumor mutation burden (TMB) has been regarded as the most popular biomarker for PAAD immunotherapy. However, it remains unclear which gene mutations affect TMB and immune response in pancreatic adenocarcinoma.MethodsThe somatic mutation images of PAAD samples were downloaded from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Based on the expression data of the TCGA and IGCC cohorts, various bioinformatics algorithms are used for evaluating the prognostic value and functional annotation of some frequently somatically mutated genes. Furthermore, the correlation between gene mutation and tumor immunity was also evaluated.ResultsThe results showed that lysine methyltransferase 2C (KMT2C) and paternally expressed 3 (PEG3) are frequently mutated genes in PAAD. Patients with KMT2C and PEG3 mutations have higher TMB severity and a lousy prognosis. In addition, the mutations of KMT2C and PEG3 genes positively regulate the metabolic and protein-related pathways in PAAD. Meanwhile, significant differences in the composition of the immune cells were observed for KMT2C and PEG3 mutations PAAD patients, for providing additional guidelines for antitumor treatments in various KMT2C and PEG3 mutation states in PAAD.ConclusionThis study reveals that KMT2C and PEG3 mutation may serve as biomarkers for predicting prognosis and guiding anti-PAAD immunotherapy for PAAD patients.

Pathologic tumor response to neoadjuvant therapy in borderline resectable pancreatic cancer

BackgroundPrevious studies have demonstrated the prognostic significance of pathologic tumor response in pancreatic adenocarcinoma following neoadjuvant therapy (NAT). The aim of this study was to determine the incidence of significant pathologic response to NAT in borderline resectable pancreatic cancer (BRPC), and association of NAT regimen and other clinico-pathologic characteristics with pathologic response. MethodsPatients with BRPC who underwent NAT and pancreatic resection between January 2012 and June 2017 were included. Pathologic response was assessed on a qualitative scale based on the College of American Pathologists grading system. Demographics and baseline characteristics, oncologic treatment, pathology, and survival outcomes were compared. ResultsSeventy-one patients were included for analysis. Four patients had complete pathologic responses (tumor regression score 0), 12 patients had marked responses (score 1), 42 had moderate responses (score 2), and 13 had minimal responses (score 3). Patients with complete or marked responses were more likely to have received neoadjuvant gemcitabine chemoradiation (62.5%, 38.1%, and 23.1% of the complete/marked, moderate, and minimal response groups, respectively; P = 0.04). Of the complete/marked, moderate, and minimal response groups, margins were negative in 75.0%, 78.6%, and 46.2% (P = 0.16); node negative disease was observed in 87.5%, 54.8%, and 15.4% (P < 0.01); and median overall survival was 50.0 months, 31.7 months, and 23.2 months (P = 0.563). Of the four patients with pathologic complete responses, three were disease-free at 66.1, 41.7 and 31.4 months, and one was deceased with metastatic liver disease at 16.9 months. ConclusionsA more pronounced pathologic tumor response to NAT in BRPC is correlated with node negative disease, but was not associated with a statistically significant survival benefit in this study.

Combined morphologic and metabolic pipeline for Positron emission tomography/computed tomography based radiotherapy response evaluation in locally advanced pancreatic adenocarcinoma.

Adaptive radiation planning for pancreatic adenocarcinoma (PA) relies on accurate treatment response assessment, while traditional response evaluation criteria inefficiently characterize tumors with complex morphological features or intrinsically low metabolism. To better assess treatment response of PA, we quantify and compare regional morphological and metabolic features of the 3D pre- and post-radiation therapy (RT) tumor models. Thirty-one PA patients with pre and post-RT Positron emission tomography/computed tomography (PET/CT) scans were evaluated. 3D meshes of pre- and post-RT tumors were generated and registered to establish vertex-wise correspondence. To assess tumor response, Mahalanobis distances (M dist∣Fusion) between pre- and post-RT tumor surfaces with anatomic and metabolic fused vectors were calculated for each patient. M dist∣Fusion was evaluated by overall survival (OS) prediction and survival risk classification. As a comparison, the same analyses were conducted on traditional imaging/physiological predictors, and distances measurements based on metabolic and morphological features only. Among all the imaging/physiological parameters, M dist∣Fusion was shown to be the best predictor of OS (HR = 0.52, p = 0.008), while other parameters failed to reach significance. Moreover, M dist∣Fusion outperformed traditional morphologic and metabolic measurements in patient risk stratification, either alone (HR = 11.51, p < 0.001) or combined with age (HR = 9.04, p < 0.001). We introduced a PET/CT-based novel morphologic and metabolic pipeline for response evaluation in locally advanced PA. The fused M dist∣Fusion outperformed traditional morphologic, metabolic, and physiological measurements in OS prediction and risk stratification. The novel fusion model may serve as a new imaging-marker to more accurately characterize the heterogeneous tumor RT response.