Serum albumin: a pharmacokinetic marker for optimizing treatment outcome of immune checkpoint blockade

Prognostic value of body mass index for first-line chemoimmunotherapy combinations in advanced non-small cell lung cancer in Chinese population

Background

Few studies have examined the correlation between body mass index (BMI) and effectiveness of first-line chemoimmunotherapy in patients with advanced non-small cell lung cancer (NSCLC); moreover, the conclusion remains elusive and no such studies have been conducted in the Chinese population. Our study aimed to validate the predictive significance of BMI in Chinese patients with advanced NSCLC receiving first-line chemoimmunotherapy combinations.

Methods

Data of patients with advanced NSCLC treated with first-line chemoimmunotherapy between June 2018 and February 2022 at three centers were retrieved retrospectively. The association between baseline BMI with progression-free survival (PFS) and overall survival (OS) was evaluated using the Kaplan-Meier method and Cox regression models. BMI was categorized according to the World Health Organization criteria.

Results

Of the included 805 patients, 5.3 % were underweight, 63.4 % had normal weight, 27.8 % were overweight, and 3.5 % were obese. Survival analysis showed that patients in the high BMI group had significantly better PFS (p = 0.012) and OS (p = 0.014) than those in the low BMI group. Further, patients in the overweight subgroup had better PFS (p = 0.036) and OS (p = 0.043) compared to the normal weight population. The results of Cox regression analysis confirmed the correlations between BMI and prognosis of advanced NSCLC patients receiving first-line chemoimmunotherapy combinations.

Conclusions

Baseline BMI affected the clinical outcomes of first-line chemoimmunotherapy combinations in patients with advanced NSCLC, and was especially favorable for the overweight subgroup.

A novel liver-function-indicators-based prognosis signature for patients with hepatocellular carcinoma treated with anti-programmed cell death-1 therapy

BACKGROUND

The liver function reserve has a significant impact on the therapeutic effects of anti-programmed cell death-1 (PD-1) for hepatocellular carcinoma (HCC). This study aimed to comprehensively evaluate the ability of liver-function-based indicators to predict prognosis and construct a novel prognostic score for HCC patients with anti-PD-1 immunotherapy.

METHODS

Between July 2018 and January 2020, patients diagnosed with HCC who received anti-PD-1 treatment were screened for inclusion in the study. The valuable prognostic liver-function-based indicators were selected using Cox proportional hazards regression analysis to build a novel liver-function-indicators-based signature (LFIS). Concordance index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and Kaplan-Meier survival curves were utilized to access the predictive performance of LFIS.

RESULTS

A total of 434 HCC patients who received anti-PD-1 treatment were included in the study. The LFIS, based on alkaline phosphatase-to-albumin ratio index, Child-Pugh score, platelet-albumin score, aspartate aminotransferase-to-lymphocyte ratio index, and gamma-glutamyl transpeptidase-to-lymphocyte ratio index, was constructed and identified as an independent risk factor for patient survival. The C-index of LFIS for overall survival (OS) was 0.692, which was higher than the other single liver-function-based indicator. The AUC of LFIS at 6-, 12-, 18-, and 24-month were 0.74, 0.714, 0.747, and 0.865 for OS, respectively. Patients in the higher-risk LFIS group were associated with both worse OS and PFS. An online and easy-to-use calculator was further constructed for better application of the LFIS signature.

CONCLUSION

The LFIS score had an excellent prognosis prediction ability superior to every single liver-function-based indicator for anti-PD-1 treatment in HCC patients. It is a reliable, easy-to-use tool to stratify risk for OS and PFS in HCC patients who received anti-PD-1 treatment.

Susceptibility of Melanoma Cells to Targeted Therapy Correlates with Protection by Blood Neutrophils

Elevated levels of peripheral blood and tumor tissue neutrophils are associated with poorer clinical response and therapy resistance in melanoma. The underlying mechanism and the role of neutrophils in targeted therapy is still not fully understood. Serum samples of patients with advanced melanoma were collected and neutrophil-associated serum markers were measured and correlated with response to targeted therapy. Blood neutrophils from healthy donors and patients with advanced melanoma were isolated, and their phenotypes, as well as their in vitro functions, were compared. In vitro functional tests were conducted through nonadherent cocultures with melanoma cells. Protection of melanoma cell lines by neutrophils was assessed under MAPK inhibition. Blood neutrophils from advanced melanoma patients exhibited lower CD16 expression compared to healthy donors. In vitro, both healthy-donor- and patient-derived neutrophils prevented melanoma cell apoptosis upon dual MAPK inhibition. The effect depended on cell-cell contact and melanoma cell susceptibility to treatment. Interference with protease activity of neutrophils prevented melanoma cell protection during treatment in cocultures. The negative correlation between neutrophils and melanoma outcomes seems to be linked to a protumoral function of neutrophils. In vitro, neutrophils exert a direct protective effect on melanoma cells during dual MAPK inhibition. This study further hints at a crucial role of neutrophil-related protease activity in protection.

Identification of C-PLAN index as a novel prognostic predictor for advanced lung cancer patients receiving immune checkpoint inhibitors

Objective

Increasing studies have highlighted the potential utility of non-invasive prognostic biomarkers in advanced lung cancer patients receiving immune checkpoint inhibitor (ICI) based anti-cancer therapies. Here, a novel prognostic predictor named as C-PLAN integrating C-reactive protein (CRP), Performance status (PS), Lactate dehydrogenase (LDH), Albumin (ALB), and derived Neutrophil-to-lymphocyte ratio (dNLR) was identified and validated in a single-center retrospective cohort.

Methods

The clinical data of 192 ICI-treated lung cancer patients was retrospectively analyzed. The pretreatment levels of CRP, PS, LDH, ALB and dNLR were scored respectively and then their scores were added up to form C-PLAN index. The correlation of C-PLAN index with the progression-free survival (PFS) or overall survival (OS) was analyzed by a Kaplan-Meier model. The multivariate analysis was used to identify whether C-PLAN index was an independent prognostic predictor.

Results

A total of 88 and 104 patients were included in the low and high C-PLAN index group respectively. High C-PLAN index was significantly correlated with worse PFS and OS in ICI-treated lung cancer patients (both p<0.001). The multivariate analysis revealed high C-PLAN index was an independent unfavorable factor affecting PFS (hazard ratio (HR)=1.821; 95%confidence interval (CI)=1.291-2.568) and OS (HR=2.058, 95%CI=1.431-2.959). The high C-PLAN index group had a significantly lower disease control rate than the low C-PLAN index group (p=0.024), while no significant difference was found for objective response rate (p=0.172). The subgroup analysis based on clinical features (pathological type, therapy strategy, TNM stage and age) confirmed the prognostic value of C-PLAN index, except for patients receiving ICI monotherapy or with age ranging from 18 to 65 years old. Finally, a nomogram was constructed based on C-PLAN index, age, gender, TNM stage and smoking status, which could predict well the 1-, 2- and 3-year survival of ICI-treated lung cancer patients.

Conclusion

The C-PLAN index has great potential to be utilized as a non-invasive, inexpensive and reliable prognostic predictor for advanced lung cancer patients receiving ICI-based anti-cancer therapies.

Refining patient selection for next-generation immunotherapeutic early-phase clinical trials with a novel and externally validated prognostic nomogram

Introduction

Identifying which patient may benefit from immunotherapeutic early-phase clinical trials is an unmet need in drug development. Among several proposed prognostic scores, none has been validated in patients receiving immunomodulating agents (IMAs)-based combinations.

Patients and methods

We retrospectively collected data of 208 patients enrolled in early-phase clinical trials investigating IMAs at our Institution, correlating clinical and blood-based variables with overall survival (OS). A retrospective cohort of 50 patients treated with IMAs at Imperial College (Hammersmith Hospital, London, UK) was used for validation.

Results

A total of 173 subjects were selected for analyses. Most frequent cancers included non-small cell lung cancer (26%), hepatocellular carcinoma (21.5%) and glioblastoma (13%). Multivariate analysis (MVA) revealed 3 factors to be independently associated with OS: line of treatment (second and third vs subsequent, HR 0.61, 95% CI 0.40-0.93, p 0.02), serum albumin as continuous variable (HR 0.57, 95% CI 0.36-0.91, p 0.02) and number of metastatic sites (<3 vs ≥3, HR 0.68, 95% CI 0.48-0.98, p 0.04). After splitting albumin value at the median (3.84 g/dL), a score system was capable of stratifying patients in 3 groups with significantly different OS (p<0.0001). Relationship with OS reproduced in the external cohort (p=0.008). Then, from these factors we built a nomogram.

Conclusions

Prior treatment, serum albumin and number of metastatic sites are readily available prognostic traits in patients with advanced malignancies participating into immunotherapy early-phase trials. Combination of these factors can optimize patient selection at study enrollment, maximizing therapeutic intent.

Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer

BACKGROUND

Malnutrition is associated with poor overall survival (OS) in breast cancer patients; however, the most predictive nutritional indicators for the prognosis of patients with breast cancer are not well-established. This study aimed to compare the predictive effects of common nutritional indicators on OS and to refine existing nutritional indicators, thereby identifying a more effective nutritional evaluation indicator for predicting the prognosis in breast cancer patients.

METHODS

This prospective study analyzed data from 776 breast cancer patients enrolled in the "Investigation on Nutritional Status and its Clinical Outcome of Common Cancers" (INSCOC) project, which was conducted in 40 hospitals in China. We used the time-dependent receiver operating characteristic curve (ROC), Kaplan-Meier survival curve, and Cox regression analysis to evaluate the predictive effects of several nutritional assessments. These assessments included the patient-generated subjective nutrition assessment (PGSGA), the global leadership initiative on malnutrition (GLIM), the controlling nutritional status (CONUT), the nutritional risk index (NRI), and the prognostic nutritional index (PNI). Utilizing machine learning, these nutritional indicators were screened through single-factor analysis, and relatively important variables were selected to modify the PNI. The modified PNI, termed the cholesterol-modified prognostic nutritional index (CPNI), was evaluated for its predictive effect on the prognosis of patients.

RESULTS

Among the nutritional assessments (including PGSGA, GLIM, CONUT, NRI, and PNI), PNI showed the highest predictive ability for patient prognosis (time-dependent ROC = 0.58). CPNI, which evolved from PNI, emerged as the superior nutritional index for OS in breast cancer patients, with the time-dependent ROC of 0.65. It also acted as an independent risk factor for mortality (p < 0.05). Moreover, the risk of malnutrition and mortality was observed to increase gradually among both premenopausal and postmenopausal age women, as well as among women categorized as non-overweight, overweight, and obese.

CONCLUSIONS

The CPNI proves to be an effective nutritional assessment tool for predicting the prognosis of patients with breast cancer.

Pretreatment albumin is a prognostic and predictive biomarker for response to atezolizumab across solid tumors

Objectives

Reliable predictive biomarkers for response to immune checkpoint inhibition (ICI) are lacking. Pretreatment serum albumin, a known prognostic and predictive factor in ICI-treated patients, has been proposed as a potential pharmacokinetic surrogate marker for anti-PD1/PD-L1 antibodies, as it shares a homeostatic pathway with IgG. However, this hypothesis is currently based on theoretical considerations and limited evidence from retrospective data. Therefore, we comprehensively investigated the prognostic and predictive value of pretreatment albumin and its relationship with anti-PD-L1 IgG levels.

Methods

We analysed pretreatment albumin and atezolizumab serum levels and clinical response in four trials (IMvigor210, IMvigor211, IMmotion151 and OAK) of patients with metastatic lung-, renal- or urothelial cancer who received atezolizumab alone or in combination.

Results

A total of 3391 patients were analysed. Correlation between serum albumin and atezolizumab levels was weak (Pearson's coefficient 0.23). We found a strong prognostic value for pretreatment serum albumin across all trials. Both atezolizumab serum levels and serum albumin were independently correlated with overall survival. Importantly, in the three randomised phase III clinical trials, the survival benefit for immunotherapy compared with the active comparator arm was limited to patients with pretreatment serum albumin > 35 g L-1.

Conclusion

Our data do not support the hypothesis that albumin serves as a surrogate for atezolizumab pharmacokinetics. However, we show that albumin on its own exerts strong prognostic value for patients treated with immunotherapy. As benefit from immunotherapy was limited to patients with normal/elevated serum albumin levels, baseline albumin could potentially be used as a predictive marker for immune checkpoint inhibition.

Identification of prognostic nutritional index as a reliable prognostic indicator for advanced lung cancer patients receiving immune checkpoint inhibitors

Background

Prognostic nutritional index (PNI) has been identified as a reliable prognostic factor for cancer adjuvant therapy. However, its prognostic value in lung cancer patients receiving immune checkpoint inhibitors (ICIs) remains inconclusive.

Method

A systematic literature review and meta-analysis was performed based on online databases before March 1th 2023. The correlation of PNI with overall survival (OS) or progression-free survival (PFS) was determined using the hazard ratios (HRs) coupled with 95% confidence intervals (CIs). Then, a retrospective cohort enrolling 123 ICI-treated lung cancer patients from two hospitals was utilized for validation and further investigation.

Results

A total of 14 studies enrolling 1,260 lung cancer patients were included in the meta-analysis. The high PNI level was significantly correlated with better OS (HR = 2.56, 95% CI = 1.86-3.54) and PFS (HR = 1.91, 95% CI = 1.53-2.40) of the lung cancer patients. The subgroup analysis confirmed the results except for the PFS in patients receiving anti-PD-1 therapy (HR = 1.51, 95% CI = 0.86-2.65). In the retrospective study, the high PNI level was identified as a favorable factor for OS and PFS not only in the whole cohort but also in the subgroups stratified by non-small cell lung cancer and small cell lung cancer. The high PNI was also correlated with better anti-cancer therapy response and performed better than body mass index and serum albumin level in OS prediction. Finally, we established a novel prognostic nomogram based on PNI and other clinical parameters. The nomogram was found to perform well in predicting the 1-year OS of ICI-treated lung cancer patients.

Conclusion

Both the meta-analysis and retrospective work demonstrate the PNI is a reliable prognostic factor for advanced lung cancer patients receiving ICI-based therapies. Our study further highlights the crucial role of nutrition assessment and intervention in cancer immunotherapy.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier: CRD42023424146.