The role of systemic immuno-inflammatory factors in resectable pancreatic adenocarcinoma: a cohort retrospective study

A Review of the Prognostic Significance of Neutrophil-to-Lymphocyte Ratio in Nonhematologic Malignancies

Biomarkers are crucial in cancer diagnostics, prognosis, and surveillance. Extensive research has been dedicated to identifying biomarkers that are broadly applicable across multiple cancer types and can be easily obtained from routine investigations such as blood cell counts. One such biomarker, the neutrophil-to-lymphocyte ratio (NLR), has been established as a prognostic marker in cancer. However, due to the dynamic nature of cancer diagnosis and treatment, periodic updates are necessary to keep abreast of the vast amount of published data. In this review, we searched the PubMed database and analyzed and synthesized recent literature (2018-February 2024) on the role of NLR in predicting clinical outcomes in nonhematologic malignancies. The search was conducted using the PubMed database. We included a total of 88 studies, encompassing 28,050 human subjects, and categorized the findings into four major groups: gastrointestinal cancer, cancers of the urinary tract and reproductive system, lung cancer, and breast cancer. Our analysis confirms that NLR is a reliable prognostic indicator in cancer, and we discuss the specific characteristics, limitations, and exceptions associated with its use. The review concludes with a concise Q&A section, presenting the most relevant take-home messages in response to five key practical questions on this topic.

Performance of nutritional and inflammatory markers in patients with pancreatic cancer

BACKGROUND

Systemic inflammation and nutrition play pivotal roles in cancer progression and can increase the risk of delayed recovery after surgical procedures.

AIM

To assess the significance of inflammatory and nutritional indicators for the prognosis and postoperative recovery of patients with pancreatic cancer (PC).

METHODS

Patients who were diagnosed with PC and underwent surgical resection at our hospital between January 1, 2019, and July 31, 2023, were enrolled in this retrospective observational cohort study. All the data were collected from the electronic medical record system. Seven biomarkers - the albumin-to-globulin ratio, prognostic nutritional index (PNI), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), nutritional risk index (NRI), and geriatric NRI were assessed.

RESULTS

A total of 446 patients with PC met the inclusion criteria and were subsequently enrolled. Patients with early postoperative discharge tended to have higher PNI values and lower SII, NLR, and PLR values (all P < 0.05). Through multivariable logistic regression analysis, the SII value emerged as an independent risk factor influencing early recovery after surgery. Additionally, both univariable and multivariable Cox regression analyses revealed that the PNI value was the strongest prognostic marker for overall survival (OS; P = 0.028) and recurrence-free survival (RFS; P < 0.001). The optimal cutoff PNI value was established at 47.30 using X-tile software. Patients in the PNI-high group had longer OS (P < 0.001) and RFS (P = 0.0028) times than those in the PNI-low group.

CONCLUSION

Preoperative systemic inflammatory-nutritional biomarkers may be capable of predicting short-term recovery after surgery as well as long-term patient outcomes.

Neutrophil-to-Lymphocyte Ratio and Prognostic Nutritional Index Are Predictors for Overall Survival after Primary Pancreatic Resection of Pancreatic Ductal Adenocarcinoma: A Single Centre Evaluation

PURPOSE

Prognostic inflammation-based parameters have been reported as useful tools in various oncologic diseases. Pancreatic ductal adenocarcinoma (PDAC) is characterized by a high mortality rate, making reliable prognostic markers highly desirable. However, there is still inconsistency in the literature regarding the efficacy of the different available scores.

METHODS

A total of 207 patients, who underwent primary resection of PDAC from January 2000 to December 2018 at the University Hospital of Erlangen, were included in this retrospective single-center study. Different biomarkers, including the preoperative neutrophil-lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), the c-reactive protein (CRP)-albumin ratio (CAR), the lymphocyte-CRP ratio (LCR), the prognostic nutritional index (PNI) and the modified Glasgow prognostic score (mGPS) were analyzed for their ability to predict overall survival (OS).

RESULTS

In our cohort, the median overall survival was 20.7 months. Among the investigated biomarkers, NLR and PNI were identified as independent prognostic markers (Hazard Ratio (HR) 1.6 (1.0-2.5), p = 0.048 and HR 0.6 (0.4-0.9), p = 0.018), whereas PLR, CAR, LCR and mGPS did not reach significance in the multivariate analysis. Subgroup analysis revealed that the prognostic value of NLR and PNI is particularly evident in locally advanced tumor stages (pT3/4 and pN+).

CONCLUSIONS

The NLR and PNI could serve as valuable tools for estimating prognosis in patients with PDAC undergoing pancreatic resection in curative intention, especially in locally advanced tumor stages. However, conflicting results in the current literature highlight the need for further prospective studies to validate these findings.

Comparative immune profiling of pancreatic ductal adenocarcinoma progression among South African patients

BACKGROUND

Pancreatic Ductal Adenocarcinoma (PDAC) is an aggressive cancer characterized by an immunosuppressive microenvironment. Patients from specific ethnicities and population groups have poorer prognoses than others. Therefore, a better understanding of the immune landscape in such groups is necessary for disease elucidation, predicting patient outcomes and therapeutic targeting. This study investigated the expression of circulating key immune cell markers in South African PDAC patients of African ancestry.

METHODS

Blood samples were obtained from a total of 6 healthy volunteers (HC), 6 Chronic Pancreatitis (CP) and 34 PDAC patients consisting of 22 resectable (RPC), 8 locally advanced (LAPC) and 4 metastatic (MPC). Real-time Quantitative Polymerase Chain reactions (RT-qPCR), Metabolomics, Enzyme-Linked Immunosorbent Assay (ELISA), Reactive Oxygen Species (ROS), and Immunophenotyping assays were conducted. Statistical analysis was conducted in R (v 4.3.2). Additional analysis of single-cell RNA data from 20 patients (16 PDAC and 4 controls) was conducted to interrogate the distribution of T-cell and Natural Killer cell populations.

RESULTS

Granulocyte and neutrophil levels were significantly elevated while lymphocytes decreased with PDAC severity. The total percentages of CD3 T-cell subpopulations (helper and double negative T-cells) decreased when compared to HC. Although both NK (p = 0.014) and NKT (p < 0.001) cell levels increased as the disease progressed, their subsets: NK CD56dimCD16- (p = 0.024) and NKTs CD56+ (p = 0.008) cell levels reduced significantly. Of note is the negative association of NK CD56dimCD16- (p < 0.001) cell levels with survival time. The gene expression analyses showed no statistically significant correlation when comparing the PDAC groups with the controls. The inflammatory status of PDAC was assessed by ROS levels of serum which were elevated in CP (p = 0.025), (RPC (p = 0.003) and LAPC (p = 0.008)) while no significant change was observed in MPC, compared to the HC group. ROS was shown to be positively correlated with GlycA (R = 0.45, p = 0.0096). Single-cell analyses showed a significant difference in the ratio of NKT cells per total cell counts in LAPC (p < 0.001) and MPC (p < 0.001) groups compared with HC, confirming observations in our sample group.

CONCLUSION

The expression of these immune cell markers observed in this pilot study provides insight into their potential roles in tumour progression in the patient group and suggests their potential utility in the development of immunotherapeutic strategies.

A novel nomogram and risk classification system based on inflammatory and immune indicators for predicting prognosis of pancreatic cancer patients with liver metastases

BACKGROUND

The study determined to construct a novel predictive nomogram to access the prognosis of pancreatic cancer patients with liver metastases (PCLM).

METHODS

Medical records included clinical and laboratory variables were collected. The patients were randomly divided into training and validation cohort. First, in the training cohort, the optimal cutoff value of SII, PNI, NLR, PLR were obtained. Then the survival analysis evaluated the effects of above indices on OS. Next, univariate and multivariate analyses were used to identify the independent factors of OS. Moreover, a nomogram was constructed based on LASSO cox analysis. Additionally, the predictive efficacy of the nomogram was evaluated by ROC curve and calibration curve in the training and validation cohort. Finally, a risk stratification system based on the nomogram was performed.

RESULTS

A total of 472 PCLM patients were enrolled in the study. The optimal cutoff values of SII, PNI, PLR and NLR were 372, 43.6, 285.7143 and 1.48, respectively. By combing SII and PNI, named coSII-PNI, we divided the patients into three groups. The Kaplan-Meier curves demonstrated above indices were correlated with OS. Univariate and multivariate analyses found the independent prognostic factors of OS. Through LASSO cox analysis, coSII-PNI, PNI, NLR, CA199, CEA, chemotherapy and gender were used to construct the nomogram. Lastly, the ROC curve and calibration curve demonstrated that the nomogram can predict prognosis of PCLM patients. Significant differences were observed between high and low groups.

CONCLUSIONS

The nomogram based on immune, inflammation, nutritional status and other clinical factors can accurately predict OS of PCLM patients.

The prognostic effect of the systemic immune-inflammation index on overall survival of periampullary cancer

OBJECTIVE

The systemic immune-inflammation index (SII) is used to assess survival in many cancers. SII has been examined separately in pancreatic head, ampulla, and distal choledochus cancers, and different cut-off values were found. Detecting the location of periampullary cancer before surgery may be difficult or misleading. This study aimed to investigate the use of SII in predicting overall survival (OS) with periampullary cancers regardless of tumor location.

METHODS

Between January 2010 and January 2020, 163 patients who underwent pancreaticoduodenectomy for periampullary tumors were assessed. After applying the exclusion criteria, data from 116 patients with cancer who underwent pancreaticoduodenectomy were included in the study.

RESULTS

OS was compared using Kaplan-Meier curves. The prognostic significance of baseline SII and other factors were assessed in univariate and multivariate analyses using the Cox proportional hazard regression model. Univariate analysis demonstrated that age ≥60.5 years (hazard ratio [HR]: 2.042, 95% CI: [1.355-3.078]; p = 0.001), male sex (HR: 1.863, 95% CI: [1.231-2.821]; p = 0.003), tumor in the pancreatic head vs. ampulla (HR: 2.150, 95% CI: [1.364-3.389]; p = 0.001), tumor in the pancreatic head vs. distal choledochus (HR: 1.945, 95% CI: [1.091-3.472]; p = 0.024), N (+) stage (HR: 1.868, 95% CI: [1.223-2.854]; p = 0.004), total bilirubin level >0.35 (HR: 2.131, 95% CI: [1.245-3.649]; p = 0.006), NLR >2.13 (HR: 1.911, 95% CI: [1.248-2.925]; p = 0.003), and SII >704 (HR: 1.966, 95% CI: [1.310-2.950]; p = 0.001) were significantly associated with OS. Multivariate analysis revealed that SII >704 (HR: 2.375; p < 0.001), age ≥ 60.5 years (HR: 2.728; p < 0.001), N-stage positivity (HR: 3.431; p < 0.001), and tumor in the pancreatic head vs. ampulla (HR: 2.801; p < 0.001) were independently associated with poor survival. There was no difference between tumor locations in terms of SII (p = 0.206).

CONCLUSIONS

SII is an independent prognostic risk factor and may be a marker for predicting OS in patients with periampullary cancer. There was no statistical difference between the tumor locations in terms of SII. A single cut-off value of SII may be used for periampullary cancer survival without the need for a pathology specimen.

The efficient circulating immunoscore predicts prognosis of patients with advanced gastrointestinal cancer

Background

Immunoscore from tumor tissues was initially established to evaluate the prognosis of solid tumor patients. However, the feasibility of circulating immune score (cIS) for the prognosis of advanced gastrointestinal cancers (AGC) has not been reported.

Material and methods

Peripheral venous blood was collected from 64 untreated AGC patients. We utilized flow cytometry to determine several immune cell subpopulations, including CD8⁺ and CD4⁺ T cells, NK cells, and CD4 + CD25 + CD127^low Tregs. The circulating immune score 1 (cIS1) was assessed according to the proportions of CD4⁺, CD8⁺ T cells, and NK cell, whereas circulating immune score 2 (cIS2) was derived from the proportions of CD4⁺, CD8⁺ T cell, and CD4 + CD25 + CD127^low Tregs. The prognostic role of cIS for progression-free survival (PFS) and overall survival (OS) was analyzed using Kaplan–Meier curves and Cox multivariate models. Receiver operating characteristic (ROC) curves were depicted to compare the prognostic values of cIS1 and cIS2.

Results

AGC patients with high cIS1(≥ 2) and cIS2(≥ 2) had significantly longer PFS (cIS1: median PFS, 11 vs. 6.7 months, P = 0.001; cIS2: 12 vs. 5.8 months, P < 0.0001) and OS (cIS1: median OS, 12 vs. 7.9 months, P = 0.0004; cIS2: 12.8 vs. 7.4 months, P < 0.0001) than those with low cIS1 and low cIS2. The areas under ROC curves (AUROCs) of cIS1 and cIS2 for OS were 0.526 (95% confidence interval; 95% CI 0.326–0.726) and 0.603 (95% CI 0.427–0.779, P = 0.332), whereas AUROC of cIS2 for PFS was larger than that of cIS1 0.735 (95% CI 0.609–0.837) vs 0.625 (95% CI 0.495–0.743) (P = 0.04)).

Conclusion

The cIS can be applied to predict the prognosis of untreated AGC patients. Compared with cIS1, cIS2 displayed superior prognostic value for PFS prediction.