Biomarker For Pancreatic Cancer Research Articles

Abstract A009: Mutant KRAS in Circulating Tumor DNA Assessed by Digit Droplet PCR as a Biomarker in Pancreatic Cancer in Patients Treated with Neoadjuvant Chemotherapy

Abstract Introduction: The detectability and prognostic significance of circulating tumor DNA (ctDNA) in patients with pancreatic ductal adenocarcinoma (PDAC) after neoadjuvant chemotherapy (NAC) is unclear. The objective of this study was to investigate the rate of detection and prognostic value of KRAS mutant ctDNA in PDAC patients after treatment with NAC as assessed by digital droplet polymerase chain reaction (ddPCR). Methods: Patients with newly diagnosed, localized, PDAC were enrolled in a prospective cohort study. Peripheral blood samples were collected at diagnosis, after NAC, and after resection. DNA was extracted from patient plasma samples using the QIAamp Circulating Nucleic Acid Kit #55114 (Qiagen N.V., Venlo Netherlands). Each sample was probed (catalog number 10049550) for KRAS codon 12 exon 2 glycine substitutions for aspartic acid (G12D), valine (G12V), and arginine (G12R). Kaplan-Meier, log-rank, and Cox regression survival analyses were performed. Results: 84 patients were included in the analysis. Patients were most commonly male (53.6%) and had tumors that were radiographically resectable (57.1%). After diagnosis, 79.8% of patients received NAC and 57.1% of patients received curative-intent surgical resection. Samples were collected for analysis from 59 (70.2%), 56 (83.6%), and 45 (93.8%) patients at diagnosis, after NAC, and after resection, respectively. Mutant KRAS ctDNA was detected in 49.3% of patients at diagnosis, 69.6% of patients after NAC, and 54.1% of patients after resection, respectively. The median OS of the cohort was 25.1 months (12.0-not reached [NR]). Detection (hazard ratio [HR] 36.8, 95% confidence interval [CI] 2.9-461.4), copy number (HR 4.0 95% CI 1.6-10.2), and percentage mutation (HR 2.9 95% CI 1.2-6.8) of KRAS G12V ctDNA after resection were all independently associated with shorter OS. Mutant KRAS ctDNA detection was not associated with and OS at other study timepoints. There were 15 (17.9%) patients that cleared mutational ctDNA over the course of treatment. Clearance of ctDNA during NAC was associated with improved overall survival (OS) (18.4 mo. vs NR). Conclusions: In patients with PDAC treated with NAC, KRAS mutations are detectable in ctDNA by ddPCR in the majority of patients over the course of treatment. Detection, copy number, and percentage mutation of KRAS G12V after NAC and resection were each independently associated with shorter OS. Clearance of ctDNA is associated with improved OS. The results demonstrate that KRAS mutant ctDNA predicts prognosis after NAC and resection. Citation Format: Dominic Vitello, Dhavan Shah, Amy Wells, Larissa Masnyk, Madison Cox, Lauren Janczewski, John Abad, Kevin Dawravoo, Arlene D'Souza, Grace Suh, Robert Bayer, Massimo Cristofanilli, David Bentrem, Yingzhe Liu, Hui Zhang, Lucas Santana-Santos, Lawrence Jennings, Qiang Zhang, Akhil Chawla. Mutant KRAS in Circulating Tumor DNA Assessed by Digit Droplet PCR as a Biomarker in Pancreatic Cancer in Patients Treated with Neoadjuvant Chemotherapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A009.

Bioinformatical and experimental validation on EFNA5 biomarker for pancreatic cancer

Pancreatic cancer is one of the most aggressive malignancies in the digestive system, characterized by vague early symptoms and rapid disease progression. Currently, treatment options for pancreatic cancer are limited, with unsatisfactory outcomes and poor prognosis, as the overall 5-year survival rate is less than 10%. Therefore, it is crucial to identify new biomarkers for pancreatic cancer.We analyzed the differential expression of EFNA5 at the mRNA level using data from the TCGA, GTEX, and GEO databases, followed by validation of EFNA5 protein expression differences through immunohistochemistry. Kaplan-Meier survival analysis and Cox regression analysis were used to explore the prognostic value of EFNA5. KEGG, GO enrichment analyses, and GSEA were employed to predict the biological functions of EFNA5. Bioinformatics algorithms were utilized to analyze the impact of EFNA5 on drug sensitivity, immune cell infiltration, and tumor mutational burden. Finally, we conducted cell phenotype experiments to investigate the effects of EFNA5 on the proliferation, migration, and invasion of pancreatic cancer cells. Bioinformatics data showed that the mRNA level of EFNA5 was higher in pancreatic cancer tissues compared to normal tissues. Immunohistochemistry experiments confirmed that the protein expression level of EFNA5 was significantly higher in pancreatic cancer tissues (n = 19) than in adjacent normal tissues (n = 19). Survival analysis indicated that the overall survival (OS) and progression-free survival (PFS) were worse in the high EFNA5 expression group compared to the low expression group. Univariate and multivariate Cox regression analyses demonstrated that EFNA5 is a risk factor affecting the prognosis of pancreatic cancer patients. KEGG pathway enrichment analysis revealed that differentially expressed genes (DEGs) between high and low EFNA5 expression groups were primarily enriched in pathways such as PI3K/Akt, axon guidance, and focal adhesion. GO enrichment analysis showed that DEGs were mainly associated with functions like epidermis development, cell adhesion, and intercellular junctions. Immune cell infiltration analysis found that EFNA5 expression was correlated with the infiltration levels of various immune cells. The tumor mutational burden was higher in the high EFNA5 expression group compared to the low expression group. Drug sensitivity analysis indicated that the high EFNA5 expression group had lower sensitivity to several commonly used chemotherapy drugs for pancreatic cancer. Cellular experiments demonstrated that knocking down EFNA5 inhibited the proliferation, invasion, and migration of pancreatic cancer cells. EFNA5 is overexpressed in pancreatic cancer tissues, and its high expression is associated with poor prognosis in pancreatic cancer patients. Downregulation of EFNA5 reduces the proliferation, migration, and invasion capabilities of the pancreatic cancer cell line BxPC-3. EFNA5 is closely related to the occurrence, development, prognosis, immune infiltration, and drug sensitivity of pancreatic cancer. Our study suggests that EFNA5 is a potential biomarker and therapeutic target.

Serum PCSK9 is a novel serological biomarker for the diagnosis and prognosis of pancreatic cancer.

Although CA19-9 is an essential blood biomarker of pancreatic cancer (PC), its sensitivity and specificity are limited for early detection. We analyzed the serum proprotein convertase subtilisin/kexin type 9 (sPCSK9) in PC patients, benign disease groups (BDG), and healthy controls (HC) by ELISA. Consistently, sPCSK9 was considerably lower in PC patients than in HC (Z = -2.546, P < 0.05), and sPCSK9 in PC patients was statistically significantly higher than in BDG (Z = -5.457, P < 0.001). sPCSK9 was linked to the invasion of lymph nodes (χ2 = 6.846, P < 0.01). According to ROC curves, combining sPCSK9 with CA19-9 could potentially enhance the diagnostic capability of CA19-9 in early-stage PC patients. Furthermore, the low sPCSK9 group (n = 41) exhibited statistically significantly prolonged overall survival compared to the high sPCSK9 group (n = 15), with median survival times of 27 months (95% CI [17.59-36.41]) and 11 months (95% CI [7.21-14.79]), respectively (P = 0.022). The diagnostic performance of CA19-9 for early-stage PC patients could be improved by combining sPCSK9 with CA19-9. Moreover, the higher sPCSK9 group has a significantly shorter overall survival rate.

Liquid-liquid phase separation-related features of PYGB/ACTR3/CCNA2/ITGB1/ATP8A1/RAP1GAP2 predict the prognosis of pancreatic cancer.

The growth and metastasis of pancreatic cancer (PC) has been found to be closely associated with liquid-liquid phase separation (LLPS). This study sought to identify LLPS-related biomarkers in PC to construct a robust prognostic model. Transcriptomic data and clinical information related to PC were retrieved from publicly accessible databases. The PC-related data set was subjected to differential expression, Mendelian randomization (MR), univariate Cox, and least absolute selection and shrinkage operator analyses to identify biomarkers. Using the biomarkers, we subsequently constructed a risk model, identified the independent prognostic factors of PC, established a nomogram, and conducted an immune analysis. The study identified four genes linked with an increased risk of PC; that is, PYGB, ACTR3, CCNA2, and ITGB1. Conversely, ATP8A1, and RAP1GAP2 were found to provide protection against PC. These findings contributed significantly to the development of a highly precise risk model in which risk, age, and pathology N stage were categorized as independent factors in predicting the prognosis of PC patients. Using these factors, a nomogram was established to predict survival outcomes accurately. An immune analysis revealed varying levels of eosinophils, gamma delta T cells, and other immune cells between the distinct risk groups. The high-risk patients exhibited increased potential for immune escape, while the low-risk patients showed a higher response to immunotherapy. Six genes were identified as having potential causal relationships with PC. These genes were integrated into a prognostic risk model, thereby serving as unique prognostic signatures. Our findings provide novel insights into predicting the prognosis of PC patients.

Single-cell analysis of chemotherapy-resistant microenvironment identifies a chemo-response biomarker for pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal, aggressive cancer due to limited response chemotherapy. The tumor microenvironment (TME) has emerged as a key player in the development of chemoresistance and in malignant progression. In this study, we hypothesized that chemotherapy response is predictable by chemotherapy-related cell types and their differentially expressed genes (DEGs). DEGs of chemoresistance cell types were identified via single cell analysis and Wilcoxon test. A chemotherapy response signature was established using a random forest model and validated with public datasets. Bulk cell fraction was analyzed using BayesPrism algorithms. Log-rank test was used to analyze survival of PDAC patients. We found that natural killer (NK) cells, myeloid cells, and erythroid cells were highly infiltrated in chemo-resistant TME. A total of 36 chemoresistance-related DEGs of chemo-resistant cells were identified in chemo-resistant PDAC. Functional enrichment analysis showed that chemoresistance upregulated various inflammation-related pathways, including TGF-β signaling. Based on these features, we constructed a random forest model to predict the response and survival for PDAC patients, which accurately distinguished high-risk and chemoresistant patients with significantly poorer prognosis in both the training and independent validation datasets. Cox regression analysis indicated that predicted labels were an independent prognostic factor in PDAC. Moreover, deconvolution of TME confirmed higher infiltration levels of M2 macrophage and NK cells in predicted chemoresistance. When combined with chemotherapy response related tumor mutations, the model showed excellent ability in predicting chemotherapy response and survival. The TME was closely associated with the chemotherapy response and prognosis of PDAC. Our TME-based random forest model predicted chemotherapy response with complementary knowledge to the response-related genetic mutations.

Combination of neutrophil-to-lymphocyte ratio and serum CA 19-9 as a prognostic factor in pancreatic cancer.

Traditionally, serum carbohydrate antigen 19-9 (CA 19-9) has been used as a key biomarker for pancreatic cancer and recently other biomarkers which reflect the systemic immune and inflammatory responses also have been explored as potential prognostic factors. The study aims to evaluate the significance of pretreatment neutrophil-to-lymphocyte ratio (NLR) and serum CA 19-9 as prognostic factor in pancreatic cancer patients. A retrospective analysis was conducted in 153 consecutive patients with pancreatic cancer in Instituto Nacional de Cancerología from 2013 to 2018. Pretreatment NLR and serum CA 19-9 values were recorded as well as survivals. The cut-off value determined for NLR was 2.4 and for serum CA 19-9 was 553 U/mL. Survival analysis showed that the 5-year overall survival (OS) was 9% in patients with low-NLR compared with 2% for patients with high-NLR (P=0.008), and 5-year progression-free survival (PFS) was 5.7% in patients with low-NLR compared with 1.3% in patients with high-NLR (P=0.007). For patients with low-CA 19.9, 5-year OS was 8.5% compared with 0% for patients with high-CA 19-9 (P=0.002), and 5-year PFS was 4.1% in patients with low-CA 19-9 compared with 0% in patients with high-CA 19-9 (P=0.005). Classification groups created showed that 5-year OS in Group 1 (low-NLR and low-CA 19-9) was 11.8% compared with 1.9% for patients in Group 2 (either one or both high-NLR or CA 19-9) (P<0.001), and 5-year PFS was 8.6% in Group 1 and 0% in Group 2 (P=0.001). High-NLR and high-CA 19-9 values used separately are both independently associated with worse OS and PFS in patients with pancreatic cancer. The classification groups created combining both biomarkers showed better prognostic significance than when used separately as demonstrated by survival analysis and multivariate analysis.

Lymphocyte antigen 6 family member E suppresses apoptosis and promotes pancreatic cancer growth and migration via Wnt/β-catenin pathway activation

Pancreatic cancer (PC) is the primary cause of cancer-related mortality. Due to the absence of reliable biomarkers for predicting prognosis or guiding treatment, there is an urgent need for molecular studies on PC. Lymphocyte antigen 6 family member E (LY6E) is implicated in uncontrolled cell growth across various cancers. However, the precise mechanism of LY6E in PC remains unclear. Here, we conducted comprehensive bioinformatic analyses using online tools and R- × 64–4.1.1, complemented by experimental validation through Western blotting, immunohistochemistry, immunosorbent assays, flow cytometry, cell assays, and animal models. Our findings reveal significantly elevated expression of LY6E in PC, correlating with poor prognosis. LY6E knockdown inhibited proliferation, invasion, and migration of PC cells, while enhancing apoptosis evidenced by increased cleaved caspase 3 levels and alterations in the Bcl-2/Bax ratio. Conversely, LY6E overexpression promoted PC cell proliferation and migration, and inhibited apoptosis. Mechanistically, LY6E downregulation suppressed the Wnt/β-catenin signaling pathway. In vivo studies demonstrated that LY6E suppression attenuated tumor growth in murine models. Additionally, LY6E suppression resulted in reduced tumor growth in mice. In conclusion, our study confirms the significant role of LY6E in the progression of PC. LY6E, serving as an independent prognostic indicator, has the potential to serve as a valuable biomarker for PC to inform treatment strategies.

Urinary microRNA-210-3p as a novel and non-invasive biomarker for the detection of pancreatic cancer, including intraductal papillary mucinous carcinoma

BackgroundThis study aims to explore novel microRNAs in urine for screening and predicting clinical characteristics in pancreatic cancer (PC) patients using a microRNA array-based approach.MethodsWe used the Toray® 3D-Gene microRNA array-based approach to compare urinary levels between PC patients and healthy volunteers.Results(1) Four oncogenic microRNAs (miR-744-5p, miR-572, miR-210-3p, and miR-575) that were highly upregulated in the urine of PC patients compared to healthy individuals were identified by comprehensive microRNA array analysis. (2) Test-scale analysis by quantitative RT-PCR for each group of 20 cases showed that miR-210-3p was significantly upregulated in the urine of PC patients compared to healthy individuals (P = 0.009). (3) Validation analysis (58 PC patients and 35 healthy individuals) confirmed that miR-210-3p was significantly upregulated in the urine of PC patients compared to healthy individuals (P < 0.001, area under the receiver operating characteristic curve = 0.79, sensitivity: 0.828, specificity: 0.743). We differentiated PC patients into invasive ductal carcinoma (IDCa) and intraductal papillary mucinous carcinoma (IPMC) groups. In addition to urinary miR-210-3p levels being upregulated in IDCa over healthy individuals (P = 0.009), urinary miR-210-3p levels were also elevated in IPMC over healthy individuals (P = 0.0018). Urinary miR-210-3p can differentiate IPMC from healthy individuals by a cutoff of 8.02 with an AUC value of 0.762, sensitivity of 94%, and specificity of 63%. (4) To test whether urinary miR210-3p levels reflected plasma miR-210-3p levels, we examined the correlation between urinary and plasma levels. Spearman’s correlation analysis showed a moderate positive correlation (ρ = 0.64, P = 0.005) between miR-210-3p expression in plasma and urine.ConclusionsUrinary miR-210-3p is a promising, non-invasive diagnostic biomarker of PC, including IPMC.Trial registrationNot applicable.

Novel diagnostic biomarkers for pancreatic cancer: assessing methylation status with epigenetic-specific peptide nucleic acid and KRAS mutation in cell-free DNA.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive tumor with a poor prognosis that poses challenges for diagnosis using traditional tissue-based techniques. DNA methylation alterations have emerged as potential and promising biomarkers for PDAC. In this study, we aimed to assess the diagnostic potential of a novel DNA methylation assay based on epigenetic-specific peptide nucleic acid (Epi-sPNA) in both tissue and plasma samples for detecting PDAC. The study involved 46 patients with PDAC who underwent surgical resection. Epi-TOP pancreatic assay was used to detect PDAC-specific epigenetic biomarkers. The Epi-sPNA allowed accurate and rapid methylation analysis without bisulfite sample processing. Genomic DNA extracted from paired normal pancreatic and PDAC tissues was used to assess the diagnostic efficacy of epigenetic biomarkers for PDAC. Subsequent validation was conducted on cell-free DNA (cfDNA) extracted from plasma samples, with 10 individuals represented in each group: PDAC, benign pancreatic cystic neoplasm, and healthy control. The combination of seven epigenetic biomarkers (HOXA9, TWIST, WT1, RPRM, BMP3, NPTX2, and BNC1) achieved 93.5% sensitivity and 96.7% specificity in discerning normal pancreatic from PDAC tissues. Plasma cfDNA, analyzed using these markers and KRAS mutations, exhibited a substantial 90.0% sensitivity, 95.0% specificity, and an overall 93.3% accuracy for discriminating PDAC. Notably, cancer antigen 19-9 and carcinoembryonic antigen both had an accuracy of 90.0%. Our study suggests that analyzing seven differentially methylated genes with KRAS mutations in cfDNA using the novel Epi-TOP pancreatic assay is a potential blood-based biomarker for the diagnosis of PDAC.

The EFNA4 gene is a potential prognostic biomarker in pancreatic cancer: a bioinformatics analysis.

Pancreatic cancer is a highly aggressive malignancy with poor prognosis, and there is an urgent need to understand its molecular mechanisms for early diagnosis and treatment. Despite surgical resection being the only effective treatment, most patients are diagnosed at an advanced stage, missing the optimal window for therapy. Identifying novel biomarkers is crucial for prognostic assessment, treatment planning, and early intervention. Ephrin A4 (EFNA4), a member of the receptor tyrosine kinase family, is involved in vascular and epithelial development via regulation of cell migration and rejection. However, the role of EFNA4 in pancreatic cancer has not been reported. Therefore, our study aimed to clarify the role of EFNA4 in pancreatic cancer through bioinformatics analysis and vitro experiments. The expression of EFNA4 and its potential value as a diagnostic and prognostic biomarker in pancreatic cancer was analyzed using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Profiling Interactive Analysis (GEPIA) database. According to the expression level of EFNA4, patients were divided into high expression group and low expression group, and the correlation between overall survival (OS) and disease-free survival (DFS) with different expression levels of EFNA4 and clinical parameters were analyzed. Subsequently, reverse-transcription quantitative polymerase chain reaction (RT-qPCR) was performed to detect EFNA4 expression. The proliferation, invasion, and cloning ability of the cells were detected via Cell Counting Kit 8 (CCK8), Transwell, and plate cloning assays, respectively. EFNA4 is highly expressed in pancreatic cancer, and upregulation of EFNA4 is associated with poor prognosis. In this study, EFNA4 expression was correlated with T stage and TNM (tumor-node-metastasis) stage of pancreatic cancer, and the median survival time and progression-free survival (PFS) were worse in those with high EFNA4 expression (394 days) than in those with low expression (525 days) [hazard ratio (HR): 1.47, 95% confidence interval (CI): 1.00-2.16, P=0.047]. In addition, EFNA4 was also found to be involved in the regulation of signal pathways such as cell adhesion, cyclic AMP, insulin secretion, pancreatic secretion, and protein digestion and absorption. In vitro experiments demonstrated that EFNA4 knockdown significantly inhibited the proliferation, cloning ability, and invasiveness of the PANC-1 and SW1990 pancreatic cancer cell lines. The abnormal expression of EFNA4 in pancreatic cancer is associated with poor prognosis. Knockout of EFNA4 gene could significantly inhibit the proliferation and invasion of pancreatic cancer cells. Therefore, EFNA4 may be one of the molecular targets for poor prognosis of patients with pancreatic cancer.

Stem cell-like circulating tumor cells identified by Pep@MNP and their clinical significance in pancreatic cancer metastasis.

The circulating tumor cells (CTCs) could be captured by the peptide functionalized magnetic nanoparticles (Pep@MNP) detection system in pancreatic ductal adenocarcinoma (PDAC). CTCs and the CXCR4 expression were detected to explore their clinical significance. The CXCR4+ CTCs, this is highly metastatic-prone stem cell-like subsets of CTCs (HM-CTCs), were found to be associated with the early recurrence and metastasis of PDAC. CTCs were captured by Pep@MNP. CTCs were identified via immunofluorescence with CD45, cytokeratin antibodies, and the CXCR4 positive CTCs were assigned to be HM-CTCs. The over-expression of CXCR4 could promote the migration of pancreatic cancer cell in vitro and in vivo. In peripheral blood (PB), CTCs were detected positive in 79.0% of all patients (49/62, 9 (0-71)/2mL), among which 63.3% patients (31/49, 3 (0-23)/2mL) were HM-CTCs positive. In portal vein blood (PVB), CTCs were positive in 77.5% of patients (31/40, 10 (0-40)/2mL), and 67.7% of which (21/31, 4 (0-15)/2mL) were HM-CTCs positive CTCs enumeration could be used as diagnostic biomarker of pancreatic cancer (AUC = 0.862), and the combination of CTCs positive and CA19-9 increase shows improved diagnostic accuracy (AUC = 0.963). in addition, PVB HM-CTCs were more accurate to predict the early recurrence and liver metastasis than PB HM-CTCs (AUC 0.825 vs. 0.787 and 0.827 vs. 0.809, respectively). The CTCs identified by Pep@MNP detection system could be used as diagnostic and prognostic biomarkers of PDAC patients. We identified and defined the CXCR4 over-expressed CTC subpopulation as highly metastatic-prone CTCs, which was proved to identify patients who were prone to suffering from early recurrence and metastasis.

Differential extracellular vesicle concentration and their biomarker expression of integrin αv/β5, EpCAM, and glypican-1 in pancreatic cancer models

Tumor-derived extracellular vesicles (EVs) show great potential as biomarkers for several diseases, including pancreatic cancer, due to their roles in cancer development and progression. However, the challenge of utilizing EVs as biomarkers lies in their inherent heterogeneity in terms of size and concentration, making accurate quantification difficult, which is highly dependent on the isolation and quantification methods used. In our study, we compared three EV isolation techniques and two EV quantification methods. We observed variations in EV concentration, with approximately 1.5-fold differences depending on the quantification method used. Interestingly, all EV isolation techniques consistently yielded similar EV quantities, overall size distribution, and modal sizes. In contrast, we found a notable increase in total EV amounts in samples from pancreatic cancer cell lines, mouse models, and patient plasma, compared to non-cancerous conditions. Moreover, individual tumor-derived EVs exhibited at least a 3-fold increase in several EV biomarkers. Our data, obtained from EVs isolated using various techniques and quantified through different methods, as well as originating from various pancreatic cancer models, suggests that EV profiling holds promise for the identification of unique and cancer-specific biomarkers in pancreatic cancer.

Rapid detection of spermine by using a cost-effective carbon nanostructured aptasensor

Spermine is a polyamine that participates in ion channel regulation and cell proliferation. It is considered a biomarker for pancreatic cancer. In this study, a carbon nanostructure-based aptasensor has been developed to rapidly detect spermine in solution by relying on Förster resonance energy transfer (FRET). The FRET donor, carbon quantum dots (CDs), are bioconjugated to aptamers specific for spermine. CDs have an average diameter of 5.0 ± 2.5 nm and have the maximum fluorescence intensity emitting at 510 nm when excited at 400 nm. Due to the π-π* interaction between DNA-based aptamer and GO, a FRET quencher, CDs bioconjugated with aptamer (CDs-aptamer) can directly attach on the surface of GO, resulting in significant FRET quenching. In the presence of spermine, GO and CDs-Aptamer separate, and the fluorescence intensity of CDs is restored. The restored fluorescence intensity of CD-aptamer can be observed when the concentration of spermine increases from 0.1 to 250 nM. The sensing system in this study could be a cost-effective, user-friendly method to quickly detect spermine, a biomarker for pancreatic cancer.

360P Prognostic nutritional index and systemic immune-inflammation index as biomarkers in metastatic pancreatic cancer

360P Prognostic nutritional index and systemic immune-inflammation index as biomarkers in metastatic pancreatic cancer

Interleukin-1α as a Potential Prognostic Biomarker in Pancreatic Cancer.

We assessed the prognostic role of pro-inflammatory cytokines of the IL-1 superfamily in patients with pancreatic cancer. This retrospective study was performed using two independent cohorts of patients with pancreatic cancer: the International Cancer Genome Consortium (ICGC, N = 267) cohort and The Cancer Genome Atlas (TCGA, N = 178) cohort. Univariate Cox regressions were used to identify prognosis-related pro-inflammatory cytokines of the IL-1 superfamily. Cytokines associated with outcome were included in a multivariate Cox model with relevant clinicopathological variables to identify prognostic biomarkers. IL-1α was the only pro-inflammatory cytokine of the IL-1 superfamily that was significantly associated with prognosis in both cohorts. In the training cohort (ICGC), the decile of patients with the lowest IL1A expression had better overall survival (HR = 1.99 [1.01-3.93], p = 0.05) and better relapse-free survival (HR = 1.85 [1.02-3.34], p = 0.04) than the group with the highest IL1A expression. The validation cohort (TCGA) confirmed these results: the decile with the lowest IL1A expression had better overall survival (HR = 3.00 [1.14-7.90], p = 0.03) and a lower risk of progression (HR = 3.11 [1.24-7.80], p = 0.01). IL1A is an independent prognostic marker and could be considered a potential therapeutic target in pancreatic cancer patients.

Long non-coding RNA LINC00930 targeting miR-6792-3p/ZBTB16 regulates the proliferation and EMT of pancreatic cancer

Emerging evidence suggests the dysregulation of long non-coding RNAs (lncRNAs) involved in pancreatic cancer (PC). However, the function of LINC00930 in PC has not been elaborated. In this study, we found that LINC00930 was significantly down-regulated in PC cell lines and tissues, and associated with tumor size, lymphatic metastasis, TNM stage and poor prognosis. According to the bioinformatics database, the downregulation of LINC00930 was a common event in PC associated with prognosis and EMT. Overexpression of LINC00930 inhibited the aggressive cancer phenotypes including proliferation, metastasis and epithelial-mesenchymal transition (EMT) of PC in vitro and in vivo. Bioinformatics and dual-luciferase reporter assay indicated that miR-6792-3p could directly bind to LINC00930. Additionally, the Zinc finger and BTB domain containing 16 (ZBTB16) was significantly declined in PC, which was predicted to be the downstream gene of miR-6792-3p. MiR-6792-3p mimic rescued the decreased proliferation, metastasis and EMT caused by ZBTB16 in PC cells. The LINC00930/miR-6792-3p/ZBTB16 axis was associated with the malignant progression and process of PC. The relative expression of LINC00930 was negatively correlated with the expression of miR-6792-3p and was closely linked with ZBTB16 levels in PC. LINC00930 might serve as a potential prognostic biomarker and therapeutic target for PC.

Multiomics integration reveals NETosis heterogeneity and TLR2 as a prognostic biomarker in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant neoplasm characterized by a poor prognosis and limited therapeutic strategy. The PDAC tumor microenvironment presents a complex heterogeneity, where neutrophils emerge as the predominant constituents of the innate immune cell population. Leveraging the power of single-cell RNA-seq, spatial RNA-seq, and multi-omics approaches, we included both published datasets and our in-house patient cohorts, elucidating the inherent heterogeneity in the formation of neutrophil extracellular traps (NETs) and revealed the correlation between NETs and immune suppression. Meanwhile, we constructed a multi-omics prognostic model that suggested the patients exhibiting downregulated expression of NETs may have an unfavorable outcome. We also confirmed TLR2 as a potent prognosis factor and patients with low TLR2 expression had more effective T cells and an overall survival extension for 6 months. Targeting TLR2 might be a promising strategy to reverse immunosuppression and control tumor progression for an improved prognosis.

Topographic analysis of pancreatic cancer by TMA and digital spatial profiling reveals biological complexity with potential therapeutic implications

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human malignancies. Tissue microarrays (TMA) are an established method of high throughput biomarker interrogation in tissues but may not capture histological features of cancer with potential biological relevance. Topographic TMAs (T-TMAs) representing pathophysiological hallmarks of cancer were constructed from representative, retrospective PDAC diagnostic material, including 72 individual core tissue samples. The T-TMA was interrogated with tissue hybridization-based experiments to confirm the accuracy of the topographic sampling, expression of pro-tumourigenic and immune mediators of cancer, totalling more than 750 individual biomarker analyses. A custom designed Next Generation Sequencing (NGS) panel and a spatial distribution-specific transcriptomic evaluation were also employed. The morphological choice of the pathophysiological hallmarks of cancer was confirmed by protein-specific expression. Quantitative analysis identified topography-specific patterns of expression in the IDO/TGF-β axis; with a heterogeneous relationship of inflammation and desmoplasia across hallmark areas and a general but variable protein and gene expression of c-MET. NGS results highlighted underlying genetic heterogeneity within samples, which may have a confounding influence on the expression of a particular biomarker. T-TMAs, integrated with quantitative biomarker digital scoring, are useful tools to identify hallmark specific expression of biomarkers in pancreatic cancer.

Differentially expressed genes associated with high metabolic tumor volume served as diagnostic markers and potential therapeutic targets for pancreatic cancer

BackgroundThe lack of distinct biomarkers for pancreatic cancer is a major cause of early-stage detection difficulty. The pancreatic cancer patient group with high metabolic tumor volume (MTV), one of the values measured from positron emission tomography—a confirmatory method and standard care for pancreatic cancer, showed a poorer prognosis than those with low MTV. Therefore, MTV-associated differentially expressed genes (DEGs) may be candidates for distinctive markers for pancreatic cancer. This study aimed to evaluate the possibility of MTV-related DEGs as markers or therapeutic targets for pancreatic cancer.MethodsTumor tissues and their normal counterparts were obtained from patients undergoing preoperative 18F-FDG PET/CT. The tissues were classified into MTV-low and MTV-high groups (7 for each) based on the MTV2.5 value of 4.5 (MTV-low: MTV2.5 < 4.5, MTV-high: MTV2.5 ≥ 4.5). Gene expression fold change was first calculated in cancer tissue compared to its normal counter and then compared between low and high MTV groups to obtain significant DEGs. To assess the suitability of the DEGs for clinical application, the correlation of the DEGs with tumor grades and clinical outcomes was analyzed in TCGA-PAAD, a large dataset without MTV information.ResultsTotal RNA-sequencing (MTV RNA-Seq) revealed that 44 genes were upregulated and 56 were downregulated in the high MTV group. We selected the 29 genes matching MTV RNA-seq patterns in the TCGA-PAAD dataset, a large clinical dataset without MTV information, as MTV-associated genes (MAGs). In the analysis with the TCGA dataset, MAGs were significantly associated with patient survival, treatment outcomes, TCGA-PAAD-suggested markers, and CEACAM family proteins. Some MAGs showed an inverse correlation with miRNAs and were confirmed to be differentially expressed between normal and cancerous pancreatic tissues. Overexpression of KIF11 and RCC1 and underexpression of ADCY1 and SDK1 were detected in ~ 60% of grade 2 pancreatic cancer patients and associated with ~ 60% mortality in stages I and II.ConclusionsMAGs may serve as diagnostic markers and miRNA therapeutic targets for pancreatic cancer. Among the MAGs, KIF11, RCC1, ADCY, and SDK1 may be early diagnostic markers.

High-throughput enrichment of portal venous circulating tumor cells for highly sensitive diagnosis of CA19-9-negative pancreatic cancer patients using inertial microfluidics

The carbohydrate antigen 19-9 (CA19-9) is commonly used as a representative biomarker for pancreatic cancer (PC); however, it lacks sensitivity and specificity for early-stage PC diagnosis. Furthermore, some patients with PC are negative for CA19-9 (<37 U/mL), which introduces additional limitations to their accurate diagnosis and treatment. Hence, improved methods to accurately detect PC stages in CA19-9-negative patients are warranted. In this study, tumor-proximal liquid biopsy and inertial microfluidics were coupled to enable high-throughput enrichment of portal venous circulating tumor cells (CTCs) and support the effective diagnosis of patients with early-stage PC. The proposed inertial microfluidic system was shown to provide size-based enrichment of CTCs using inertial focusing and Dean flow effects in slanted spiral channels. Notably, portal venous blood samples were found to have twice the yield of CTCs (21.4 cells per 5 mL) compared with peripheral blood (10.9 CTCs per 5 mL). A combination of peripheral and portal CTC data along with CA19-9 results showed to greatly improve the average accuracy of CA19-9-negative PC patients from 47.1% with regular CA19-9 tests up to 87.1%. Hence, portal venous CTC-based microfluidic biopsy can be used with high sensitivity and specificity for the diagnosis of early-stage PC, particularly in CA19-9-negative patients.