Predictive Value of Neutrophils Count for Local Tumor Control After Chemoradiotherapy in Patients With Locally Advanced Pancreatic Carcinoma

C-reactive protein is a prognostic biomarker in pancreatic ductal adenocarcinoma patients

AIM

The 5-year survival rate of pancreatic ductal adenocarcinoma (PDAC) is approximately 11% and has only improved marginally over the last three decades. For operable PDAC, resection and adjuvant FOLFIRINOX chemotherapy is standard of care. There is growing interest in perioperative regimens to improve outcomes. The non-randomized Phase II study "Gemcitabine and Abraxane for resectable Pancreatic cancer" (GAP) demonstrated the feasibility of perioperative gemcitabine/abraxane. Long-term survival in PDAC requires an effective immune response; hence, we undertook this translational study of the GAP trial cohort to identify immune-oncology biomarkers for clinical use.

METHODS

We combined Nanostring nCounter technology with immunohistochemistry to investigate the correlation between gene expression and overall patient survival. Findings were investigated in samples from the International Cancer Genome Consortium (ICGC, n = 88) and the Australian Pancreatic Genome Initiative (APGI, n = 227).

RESULTS

We confirmed that human equilibrative nucleoside transporter 1 (hENT1) expression was not a prognostic marker in PDAC but patients with high levels of hENT1 were more likely to live longer than 24 months post-surgery. Additionally, CD274 (PD-L1) and two novel biomarkers of survival, cathepsin W (CTSW) and C-reactive protein (CRP), were identified in the GAP cohort (n = 19). CRP expression was confirmed in data from the ICGC. Although PD-L1 and CTSW proteins were not significant across all three cohorts, results show that low CRP mRNA and protein expression are associated with longer overall survival in all three patient groups.

CONCLUSION

PDAC patients with long survival have higher hENT1 expression levels. Furthermore, CRP expression is a biomarker of poor prognosis following perioperative chemotherapy and resection in PDAC patients and thus may be useful for identifying patients who could benefit from more aggressive adjuvant strategies.

Construction of the prediction model for multiple myeloma based on machine learning

INTRODUCTION

The global burden of multiple myeloma (MM) is increasing every year. Here, we have developed machine learning models to provide a reference for the early detection of MM.

METHODS

A total of 465 patients and 150 healthy controls were enrolled in this retrospective study. Based on the variable screening strategy of least absolute shrinkage and selection operator (LASSO), three prediction models, logistic regression (LR), support vector machine (SVM), and random forest (RF), were established combining complete blood count (CBC) and cell population data (CPD) parameters in the training set (210 cases), and were verified in the validation set (90 cases) and test set (165 cases). The performance of each model was analyzed using receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis (DCA). Accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the ROC curve (AUC) were applied to evaluate the models. Delong test was used to compare the AUC of the models.

RESULTS

Six parameters including RBC (1012/L), RDW-CV (%), IG (%), NE-WZ, LY-WX, and LY-WZ were screened out by LASSO to construct the model. Among the three models, the AUC of RF model in the training set, validation set, and test set were 0.956, 0.892, and 0.875, which were higher than those of LR model (0.901, 0.849, and 0.858) and SVM model (0.929, 0.868, and 0.846). Delong test showed that there were significant differences among the models in the training set, no significant differences in the validation set, and significant differences only between SVM and RF models in the test set. The calibration curve and DCA showed that the three models had good validity and feasibility, and the RF model performed best.

CONCLUSION

The proposed RF model may be a useful auxiliary tool for rapid screening of MM patients.

Novel biomarkers to predict treatment response and prognosis in locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapy

PURPOSE

To identify genes associated with treatment response and prognosis for locally advanced rectal cancer (LARC) patients receiving neoadjuvant chemoradiotherapy (NCRT).

METHODS

In our cohort, gene expression profiles of 64 tumor biopsy samples before NCRT were examined and generated. Weighted gene co-expression network analysis was performed to identify gene modules. External validation datasets included GSE3493, GSE119409, and GSE133057. The expression of candidate genes was evaluated using immunohistochemistry (IHC). TIMER was used to assess immune infiltration.

RESULTS

We identified and validated the capability to predict the treatment response of CCT5 and ELF1 using our data and external validation datasets. The trends of survival differences of candidate genes in the GSE133057 dataset were similar to our cohort. High levels of CCT5 and ELF1 expression were associated with NCRT resistance and poor prognosis. Furthermore, the expression of CCT5 and ELF1 were also assessed in 117 LARC patients' samples by the IHC method. Based on IHC results and Cox analysis, the risk score model with CCT5 and ELF1 was constructed and performed well. The risk score was an independent prognostic factor for progression-free survival and overall survival in LARC patients and was then used to build nomogram models. The underlying mechanisms of CCT5 and ELF1 were explored using gene set enrichment analysis. The underlying pathway including apoptosis, cell cycle, and other processes. CCT5 and ELF1 expressions were significantly correlated with immune cell infiltration.

CONCLUSION

CCT5 and ELF1 were determined as biomarkers for treatment response and prognosis in LARC patients. The risk score model and nomograms helped predict treatment response and survival outcomes for LARC patients undergoing NCRT.

Immunosuppression, immune escape, and immunotherapy in pancreatic cancer: focused on the tumor microenvironment

Pancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer, is characterized by poor treatment response and low survival time. The current clinical treatment for advanced PDAC is still not effective. In recent years, the research and application of immunotherapy have developed rapidly and achieved substantial results in many malignant tumors. However, the translational application in PDAC is still far from satisfactory and needs to be developed urgently. To carry out the study of immunotherapy, it is necessary to fully decipher the immune characteristics of PDAC. This review summarizes the recent progress of the tumor microenvironment (TME) of PDAC and highlights its link with immunotherapy. We describe the molecular cues and corresponding intervention methods, collate several promising targets and progress worthy of further study, and put forward the importance of integrated immunotherapy to provide ideas for future research of TME and immunotherapy of PDAC.

Post-radiation neutrophil-to-lymphocyte ratio is a prognostic marker in patients with localized pancreatic adenocarcinoma treated with anti-PD-1 antibody and stereotactic body radiation therapy

PURPOSE

To investigate the role of pre- and post-stereotactic body radiation therapy (SBRT) neutrophil-to-lymphocyte ratio (NLR) in patients with localized pancreatic cancer treated with anti-PD-1 (programmed cell death protein-1) antibody and SBRT.

MATERIALS AND METHODS

This was a retrospective review of 68 patients with borderline resectable or locally advanced pancreatic cancer treated with anti-PD-1 antibody and SBRT after multi-agent chemotherapy. Immunotherapy was administered with 5-fraction SBRT in the neoadjuvant, concurrent, or adjuvant/maintenance setting. Clinical outcomes included overall survival (OS), local progression-free survival, distant metastasis-free survival, and progression-free survival. Median pre- and post-SBRT peripheral blood markers were compared with the Mann-Whitney U test. Univariate and multivariable analyses (UVA and MVA) were performed to identify variables associated with clinical outcomes. Linear regression was performed to determine correlations between variables and peripheral blood markers.

RESULTS

A total of 68 patients were included in the study. The percent change between median pre- and post-SBRT absolute lymphocyte count (ALC), absolute neutrophil count, and NLR were -36.0% (p < 0.001), -5.6% (p = 0.190), and +35.7% (p = 0.003), respectively. Median OS after SBRT was 22.4 months. On UVA, pre-SBRT CA19-9 (hazard ratio [HR] = 1.001; 95% confidence interval [CI], 1.000-1.001; p = 0.031), post-SBRT ALC (HR = 0.33; 95% CI, 0.11-0.91; p = 0.031), and post-SBRT NLR (HR = 1.13; 95% CI, 1.04-1.22; p = 0.009) were associated with OS. On MVA, induction chemotherapy duration (HR = 0.75; 95% CI, 0.57-0.99; p = 0.048) and post-SBRT NLR (HR = 1.14; 95% CI, 1.04-1.23; p = 0.002) predicted for OS. Patients with post-SBRT NLR ≥3.2 had a median OS of 15.6 months versus 27.6 months in patients with post-SBRT NLR <3.2 (p = 0.009). On MVA linear regression, log10CTV had a negative correlation with post-SBRT ALC (regression coefficient = -0.314; 95% CI, -0.626 to -0.003; p = 0.048).

CONCLUSION

Elevated NLR after SBRT is primarily due to depletion of lymphocytes and associated with worse survival outcomes in localized pancreatic cancer treated with anti-PD-1 antibody. Larger CTVs were associated with decreased post-SBRT ALC.

High neutrophil-to-lymphocyte ratio following stereotactic body radiation therapy is associated with poor clinical outcomes in patients with borderline resectable and locally advanced pancreatic cancer

Background

The purpose of this study is to report on the prognostic role of pre- and post-stereotactic body radiation therapy (SBRT) neutrophil-to-lymphocyte ratio (NLR) in a cohort of patients with borderline resectable (BRPC) and locally advanced pancreatic cancer (LAPC) who was treated with multi-agent induction chemotherapy followed by five-fraction SBRT.

Methods

Patients treated with multi-agent induction chemotherapy followed by SBRT from August 2016 to January 2019 and who had laboratory values available for review were included in the study. Univariate (UVA) and multivariate analyses (MVA) were performed to determine associations between pre-/post-SBRT NLR and overall survival (OS), local progression-free survival (LPFS), distant metastasis-free survival (DMFS), and progression-free survival (PFS).

Results

A total of 156 patients were treated with multi-agent induction chemotherapy followed by SBRT and had laboratory values available for review. On UVA, chemotherapy duration ≥4 months, poorly differentiated disease, inability to undergo resection, pre-SBRT ANC ≥3.7 No./µL, pre-SBRT NLR ≥2.3, and post-SBRT NLR ≥2.6 were associated with worse OS. Patients with post-SBRT NLR ≥2.6 had a median OS of 16.7 months versus median OS not yet reached in patients with post-SBRT <2.6 (P=0.009). On MVA, poorly differentiated disease [hazard ratio (HR) =1.82, 95% CI: 1.04-3.18, P=0.035], inability to undergo resection (HR =2.17, 95% CI: 1.25-3.70, P=0.006), and post-SBRT NLR ≥2.6 (HR =2.55, 95% CI: 1.20-5.45, P=0.015) were associated with inferior OS. On UVA, baseline CA 19-9 ≥219 U/mL, pre-SBRT platelet count ≥157×1,000/µL, and post-SBRT NLR ≥2.6 were associated with inferior LPFS. Patients with post-SBRT NLR ≥2.6 had a median LPFS of 18.3 months versus median LPFS not yet reached in patients with post-SBRT <2.6 (P=0.028). On MVA, only post-SBRT NLR ≥2.6 was associated with worse LPFS (HR =3.22, 95% CI: 1.04-9.98, P=0.043).

Conclusions

Post-SBRT NLR ≥2.6 predicted for inferior OS and LPFS in BRPC/LAPC patients treated with multi-agent chemotherapy and SBRT. These findings highlight the importance of further elucidating the immunologic effects of radiation therapy in this setting, which may have significant implications on both radiation design as well as combination strategies.

Neutrophil in the Pancreatic Tumor Microenvironment

Pancreatic ductal adenocarcinoma (PDAC) is a malignancy with a poor prognosis and low survival rates. PDAC is characterized by a fibroinflammatory tumor microenvironment enriched by abundant fibroblasts and a variety of immune cells, contributing to its aggressiveness. Neutrophils are essential infiltrating immune cells in the PDAC microenvironment. Recent studies have identified several cellular mechanisms by which neutrophils are recruited to tumor lesion and promote tumorigenesis. This review summarizes the current understanding of the interplay between neutrophils, tumor cells, and other components in the PDAC tumor microenvironment. The prognosis and therapeutic implications of neutrophils in PDAC are also discussed.