The Role of the Lymphocyte Functional Crosstalk and Regulation in the Context of Checkpoint Inhibitor Treatment-Review

Systemic immune-inflammation index: A new marker in differentiation of different thyroid diseases

Inflammation plays an important role in the pathogenesis of many cancer types and is associated with thyroid malignancy. The systemic immune-inflammation index (SII) is a new inflammation marker that can be calculated from routine complete blood count (CBC). This study investigated the association between SII, a marker derived from routine CBC, and different thyroid diseases. The objective was to determine if this simple inflammation marker can distinguish between benign and malignant thyroid diseases. The medical records of all patients who underwent surgical treatment for thyroid disease between January 2018 and January 2022 were systematically evaluated. The routine preoperative CBC parameters' demographic, clinical, and laboratory data were recorded. A total of 241 patients were included in the study, and the patients were grouped as having multinodular goiter (n = 125), lymphocytic thyroiditis (n = 44), and papillary thyroid carcinoma (PTC) (n = 73) according to pathological results. The SII was defined as the ratio of the total count of neutrophils × platelets divided by the lymphocyte count. Subgroup analysis of patients was performed according to the presence of follicular variant or thyroiditis, micro or macro carcinoma, or bilaterality of the tumor. The SII level was significantly higher in the PTC group than in the lymphocytic thyroiditis and multinodular goiter groups (P < .001). When we grouped the patients according to the presence of PTC as benign or malignant, the optimum cutoff point for SII level was found 654.13, with 73.8% sensitivity and 72.3% specificity from ROC analysis. In the subgroup analysis of patients with PTC, the SII level was similar according to the clinicopathological characteristics of the tumor. The differential diagnosis of thyroid diseases is important for patient management. We found that preoperative SII levels were significantly elevated in patients with PTC compared to those with benign thyroid disorders, and this simple marker can be used for the differentiation of benign and malignant thyroid disease.

Efficacy and safety of immune checkpoint inhibitors for hepatocellular carcinoma patients with macrovascular invasion or extrahepatic spread: a systematic review and meta-analysis of 54 studies with 6187 hepatocellular carcinoma patients

BACKGROUND AND AIMS

The impacts of macrovascular invasion (MVI) or extrahepatic spread (EHS) on the efficacy and safety of immune checkpoint inhibitors (ICIs) among hepatocellular carcinoma (HCC) patients remain unclear. Thus, we conducted a systematic review and meta-analysis to clarify whether ICI therapy is a feasible treatment option for HCC with MVI or EHS.

METHODS

Eligible studies published before September 14, 2022, were retrieved. In this meta-analysis, the objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and occurrence of adverse events (AEs) were outcomes of interest.

RESULTS

Fifty-four studies involving 6187 individuals were included. The findings indicated that the presence of EHS in ICI-treated HCC patients may indicate an inferior ORR (OR 0.77, 95% CI 0.63-0.96), but may not significantly affect the PFS (multivariate analyses: HR 1.27, 95% CI 0.70-2.31) and OS (multivariate analyses: HR 1.23, 95% CI 0.70-2.16). Additionally, the presence of MVI in ICI-treated HCC patients may not have significant prognostic impact on ORR (OR 0.84, 95% CI 0.64-1.10), but may indicate inferior PFS (multivariate analyses: HR 1.75, 95% CI 1.07-2.84) and OS (multivariate analyses: HR 2.03, 95% CI 1.31-3.14). The presence of EHS or MVI in ICI-treated HCC patients may not significantly impact the occurrence of any serious immune-related adverse events (irAEs) (grades ≥ 3) (EHS: OR 0.44, 95% CI 0.12-1.56; MVI: OR 0.68, 95% CI 0.24-1.88).

CONCLUSION

The presence of MVI or EHS in ICI-treated HCC patients may not significantly impact the occurrence of serious irAEs. However, the presence of MVI (but not EHS) in ICI-treated HCC patients may be a significant negative prognostic factor. Therefore, ICI-treated HCC patients with MVI warrant more attention.

Role of Exosomes in Immunotherapy of Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma is one of the most lethal malignancies, having a significantly poor prognosis. Immunotherapy, as an emerging tumor treatment option, provides new hope for many cancer patients. However, a large proportion of patients do not benefit from immunotherapy. As a critical cell-to-cell communication mediator in the tumor immune microenvironment, exosomes may play a unique role in hepatocellular carcinoma immune response and thus affect the efficiency of immunotherapy. In this review, we discuss related research on the roles of exosomes in the current immunotherapy resistance mechanism of hepatocellular carcinoma. Furthermore, we also clarify the excellent predictive value of exosomes and the roles they play in improving immunotherapy efficacy for hepatocellular carcinoma patients. We hope that our review can help readers to gain a more comprehensive understanding of exosomes’ roles in hepatocellular carcinoma immunotherapy.

Abstract

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies, having a significantly poor prognosis and no sufficiently efficient treatments. Immunotherapy, especially immune checkpoint inhibitors (ICIs), has provided new therapeutic approaches for HCC patients. Nevertheless, most patients with HCC do not benefit from immunotherapy. Exosomes are biologically active lipid bilayer nano-sized vesicles ranging in size from 30 to 150 nm and can be secreted by almost any cell. In the HCC tumor microenvironment (TME), numerous cells are involved in tumor progression, and exosomes—derived from tumor cells and immune cells—exhibit unique composition profiles and act as intercellular communicators by transporting various substances. Showing the dual characteristics of tumor promotion and suppression, exosomes exert multiple functions in shaping tumor immune responses in the crosstalk between tumor cells and surrounding immune cells, mediating immunotherapy resistance by affecting the PD-1/PD-L1 axis or the anti-tumor function of immune cells in the TME. Targeting exosomes or the application of exosomes as therapies is involved in many aspects of HCC immunotherapies (e.g., ICIs, tumor vaccines, and adoptive cell therapy) and may substantially enhance their efficacy. In this review, we discuss the impact of exosomes on the HCC TME and comprehensively summarize the role of exosomes in immunotherapy resistance and therapeutic application. We also discuss the potential of exosomes as biomarkers for predicting the efficacy of immunotherapy to help clinicians in identifying HCC patients who are amenable to immunotherapies.

The Predictive Potential of the Baseline C-Reactive Protein Levels for the Efficiency of Immune Checkpoint Inhibitors in Cancer Patients: A Systematic Review and Meta-Analysis

Background

The relationship between baseline C-reactive protein (CRP) level and the prognosis of cancer patients receiving immune checkpoint inhibitor (ICI) treatment remains controversial. The aim of this meta-analysis was to clarify whether baseline CRP level can serve as a biomarker to predict the efficiency of ICI therapy.

Methods

All associated articles published in the Cochrane Library, EMBASE, and PubMed databases from the inception of the database to December 30, 2021, were retrieved. Progression-free survival (PFS) and overall survival (OS) outcomes were meta-analyzed using the random-effects model and adjusted using the trim-and-fill method because of publication bias.

Results

Thirty-three studies (6,124 patients) conducted between 2013 and 2021 were identified. The pooled outcomes implied that high baseline CRP level patients had significantly worse OS (adjusted pooled value for univariate and multivariate analysis outcomes: HR = 1.48, 95% CI = 1.41-1.56; HR = 1.46, 95% CI = 1.34-1.59) and PFS (adjusted pooled value for univariate and multivariate analysis outcomes: HR = 1.29, 95% CI = 1.15-1.45; HR = 1.20, 95% CI = 1.02-1.40) than low baseline CRP level patients, irrespective of cancer or ICI type. Further analysis indicated that 1 mg/dl was appropriate as a cutoff value for determining the low or high level of baseline CRP to predict the OS or PFS of cancer patients receiving ICI treatment (univariate analysis: HR = 1.56, 95% CI = 1.24-1.97, P = 0.909; multivariate analysis: HR = 1.58, 95% CI = 1.23-2.03, P = 0.521).

Conclusions

High baseline CRP level (>1 mg/dl) may be an indicator for worse OS and PFS of cancer patients treated with ICIs. More high-quality prospective studies are warranted to assess the predictive value of CRP for ICI treatment.

The Prediction Potential of the Pretreatment Lung Immune Prognostic Index for the Therapeutic Outcomes of Immune Checkpoint Inhibitors in Patients With Solid Cancer: A Systematic Review and Meta-Analysis

Background

The lung immune prognostic index (LIPI) is recently developed to predict immune checkpoint inhibitors (ICIs) treatment outcomes for non-small cell lung cancer. However, its predictive value for other types of cancer remained unclear. This meta-analysis aimed to evaluate the association between pretreatment LIPI score and therapeutic outcomes in cancer patients treated with ICIs.

Methods

We searched PubMed, Cochrane Library literature databases and EMBASE for abstracts and full-text articles published from the inception of the database until 16th, Nov 2020. Meta-analyses were performed separately for progression-free survival (PFS) and overall survival (OS) by using the random-effects model.

Results

A total of 12 studies involving 4883 patients receiving ICIs treatment were identified for the primary analysis. The pooled results implied that compared with good LIPI score groups, patients with poor or intermediate LIPI score were significantly associated with worse OS (HR=3.33, 95%CI 2.64-4.21, P < 0.001, I² = 64.2%; HR=1.71, 95%CI 1.43-2.04, P < 0.001, I² = 43.6%, respectively) and PFS (HR=2.73,95%CI 2.00-3.73, P < 0.001, I² = 78.2%; HR=1.43, 95%CI 1.28-1.61, P < 0.001, I² = 16.3%, respectively). Also, for 1873 patients receiving chemotherapy, a poor LIPI score was significantly associated with worse OS (HR=2.30, 95%CI 1.73-3.07, P < 0.001; I² = 56.2%) and PFS (HR=1.92,95%CI 1.69-2.17; P < 0.001; I² = 0.0%) compared with good LIPI score groups.

Conclusions

A good LIPI score was significantly correlated with improved OS and PFS in cancer patients receiving ICIs or chemotherapy, regardless of the types of cancer.

The systemic immune-inflammation index-based model is an effective biomarker on predicting central lymph node metastasis in clinically nodal-negative papillary thyroid carcinoma

Background

A high proportion of papillary thyroid carcinoma (PTC) patients are involved in central lymph node metastasis (CLNM) with preoperative imaging examinations showing clinically nodal-negative (cN0). Meanwhile, many inflammatory biomarkers are also proven as effective factors to predict the outcomes of cancer patients and tumor progression. Thus, the values of these factors are investigated to help detecting CLNM in cN0 PTC patients.

Methods

406 cN0 PTC patients who underwent curative surgery were retrospectively analyzed. CLNM was determined by histopathological examination following the thyroidectomy. Multiple inflammatory biomarkers were comprehensively researched.

Results

A total of 406 consecutive patients were eventually included. The univariate and multivariate analyses revealed that age (OR: 0.924, 95% CI: 0.909, 0.940), gender (OR: 1.781, 95% CI: 1.060, 2.993), location of tumors (OR: 2.229, 95% CI: 1.228, 4.046) and level of systemic immune-inflammation index (SII) (OR: 1.005, 95% CI: 1.004, 1.006) were independently associated with CLNM in cN0 PTC patients, and the SII-based predictive model was constructed using these four factors. Receiver operating characteristic (ROC) curves showed significant results of the SII-based predictive model in PTC cohort with area under curve (AUC) as 0.814 (95% CI: 0.771-0.857) and in PTMC subgroup with AUC as 0.803 (95% CI: 0.752-0.854).

Conclusions

The SII-based model can effectively help predicting CLNM in both cN0 PTC patients and cN0 PTMC patients.