Independent expression of circulating and tissue levels of PD-L1: correlation of clusters with tumor metabolism and outcome in patients with non-small cell lung cancer

Diagnostic value of programmed cell death-ligand 1 expression on circulating tumor cells in lung cancer: A systematic review and meta-analysis

The expression of programmed cell death-ligand 1 (PD-L1) on circulating tumor cells offers a noninvasive method for the detection of PD-L1 expression in lung cancer, and could serve as a potential surrogate for cancer tissue. However, discrepant results make it difficult to apply PD-L1 on circulating tumor cells to clinical practice. Therefore, we conducted a meta-analysis to investigate the diagnostic value of PD-L1 on circulating tumor cells in lung cancer. To identify the relationship between the expression of PD-L1 on circulating tumor cells and lung cancer, the PubMed, Web of Science, Embase, China National Knowledge Infrastructure, and Wanfang databases were searched from inception to March 2023. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and the corresponding 95% confidence intervals were calculated to assess the diagnostic performance of PD-L1. We also conducted subgroup and sensitivity analyses. A total of 11 studies including 472 lung cancer patients were included in our study. The overall performance in terms of pooled sensitivity and specificity was 0.72 (0.52-0.86) and 0.54 (0.25-0.81), respectively. The positive likelihood ratio, negative likelihood ratio, and area under the curve were 1.57 (0.87-2.84), 0.52 (0.30-0.90), and 0.70 (0.66-0.74), respectively. Deeks' funnel plot test indicated no publication bias. Our analysis demonstrated that positive PD-L1 expression on circulating tumor cells (CTCs) exhibited a moderate diagnostic value in lung cancer, and CTCs may serve as a feasible alternative tissue analysis for the detection of PD-L1 in lung cancer.

Combination of tumor asphericity and an extracellular matrix-related prognostic gene signature in non-small cell lung cancer patients

One important aim of precision oncology is a personalized treatment of patients. This can be achieved by various biomarkers, especially imaging parameters and gene expression signatures are commonly used. So far, combination approaches are sparse. The aim of the study was to independently validate the prognostic value of the novel positron emission tomography (PET) parameter tumor asphericity (ASP) in non small cell lung cancer (NSCLC) patients and to investigate associations between published gene expression profiles and ASP. This was a retrospective evaluation of PET imaging and gene expression data from three public databases and two institutional datasets. The whole cohort comprised 253 NSCLC patients, all treated with curative intent surgery. Clinical parameters, standard PET parameters and ASP were evaluated in all patients. Additional gene expression data were available for 120 patients. Univariate Cox regression and Kaplan-Meier analysis was performed for the primary endpoint progression-free survival (PFS) and additional endpoints. Furthermore, multivariate cox regression testing was performed including clinically significant parameters, ASP, and the extracellular matrix-related prognostic gene signature (EPPI). In the whole cohort, a significant association with PFS was observed for ASP (p < 0.001) and EPPI (p = 0.012). Upon multivariate testing, EPPI remained significantly associated with PFS (p = 0.018) in the subgroup of patients with additional gene expression data, while ASP was significantly associated with PFS in the whole cohort (p = 0.012). In stage II patients, ASP was significantly associated with PFS (p = 0.009), and a previously published cutoff value for ASP (19.5%) was successfully validated (p = 0.008). In patients with additional gene expression data, EPPI showed a significant association with PFS, too (p = 0.033). The exploratory combination of ASP and EPPI showed that the combinatory approach has potential to further improve patient stratification compared to the use of only one parameter. We report the first successful validation of EPPI and ASP in stage II NSCLC patients. The combination of both parameters seems to be a very promising approach for improvement of risk stratification in a group of patients with urgent need for a more personalized treatment approach.

Targeting glycolysis in non-small cell lung cancer: Promises and challenges

Metabolic disturbance, particularly of glucose metabolism, is a hallmark of tumors such as non-small cell lung cancer (NSCLC). Cancer cells tend to reprogram a majority of glucose metabolism reactions into glycolysis, even in oxygen-rich environments. Although glycolysis is not an efficient means of ATP production compared to oxidative phosphorylation, the inhibition of tumor glycolysis directly impedes cell survival and growth. This review focuses on research advances in glycolysis in NSCLC and systematically provides an overview of the key enzymes, biomarkers, non-coding RNAs, and signaling pathways that modulate the glycolysis process and, consequently, tumor growth and metastasis in NSCLC. Current medications, therapeutic approaches, and natural products that affect glycolysis in NSCLC are also summarized. We found that the identification of appropriate targets and biomarkers in glycolysis, specifically for NSCLC treatment, is still a challenge at present. However, LDHB, PDK1, MCT2, GLUT1, and PFKM might be promising targets in the treatment of NSCLC or its specific subtypes, and DPPA4, NQO1, GAPDH/MT-CO1, PGC-1α, OTUB2, ISLR, Barx2, OTUB2, and RFP180 might be prognostic predictors of NSCLC. In addition, natural products may serve as promising therapeutic approaches targeting multiple steps in glycolysis metabolism, since natural products always present multi-target properties. The development of metabolic intervention that targets glycolysis, alone or in combination with current therapy, is a potential therapeutic approach in NSCLC treatment. The aim of this review is to describe research patterns and interests concerning the metabolic treatment of NSCLC.

Relevance of Circulating Tumor Cells as Predictive Markers for Cancer Incidence and Relapse

Shedding of cancer cells from the primary site or undetectable bone marrow region into the circulatory system, resulting in clinically overt metastasis or dissemination, is the hallmark of unfavorable invasive cancers. The shed cells remain in circulation until they extravasate to form a secondary metastatic lesion or undergo anoikis. The circulating tumor cells (CTCs) found as single cells or clusters carry a plethora of information, are acknowledged as potential biomarkers for predicting cancer prognosis and cancer progression, and are supposed to play key roles in determining tailored therapies for advanced diseases. With the advent of novel technologies that allow the precise isolation of CTCs, more and more clinical trials are focusing on the prognostic and predictive potential of CTCs. In this review, we summarize the role of CTCs as a predictive marker for cancer incidence, relapse, and response to therapy.

Negative Correlation Between 18F-RGD Uptake via PET and Tumoral PD-L1 Expression in Non-Small Cell Lung Cancer

PURPOSE

We investigated the correlation of ¹⁸F-AlF-NOTAPRGD2 (¹⁸F-RGD) uptake during positron emission tomography (PET) with tumoral programmed death-ligand 1 (PD-L1) expression and explored its potential in immune checkpoint inhibitor treatment.

METHODS

Forty-two mice were subcutaneously injected with CMT-167 lung carcinoma cells. A total of 30 mice with good growth tumor and good general condition were selected. ¹⁸F-RGD PET scanning was performed on days 0, 2, 4, 6, 9, and 11 with five mice per day. Immunohistochemistry (IHC) for PD-L1 was performed on each specimen obtained from tumors. Thirty patients with advanced non-small cell lung cancer (NSCLC) were scanned using ¹⁸F-RGD PET/CT, and Milliplex multifactor detection analyzed serum PD-1/PD-L1 expression of twenty-eight of them. Thirteen of them were analyzed immunohistochemically using core needle biopsy samples obtained from primary tumors.

RESULTS

Thirty mice were scanned by ¹⁸F-RGD PET/CT and analyzed for PD-L1 expression in tumor cells by IHC finally. Maximum standard uptake value (SUVmax) and mean SUV (SUVmean) were significantly lower in relatively-higher-PD-L1-expression tumors than in relatively-low-PD-L1-expression tumors (P < 0.05). In patients, the SUVmax was significantly negatively correlated with tumoral PD-L1 expression by IHC (P=0.014). SUVmean, peak SUV (SUVpeak), and gross tumor volume (GTV) were also negatively correlated with PD-L1, but without significance (P > 0.05). SUVmax, SUVmean, SUVpeak, and GTV were negatively correlated with serum PD-1 and PD-L1, but not significantly. According to the receiver operating characteristic curve analysis, significant correlations between SUVmax and tumoral PD-L1 expression in both mice and patients were present (P < 0.05).

CONCLUSION

Higher ¹⁸F-RGD uptake is correlated with depressed PD-L1 expression in tumor cells, and SUVmax is the best parameter to display tumoral expression of PD-L1. ¹⁸F-RGD PET may be useful for reflecting the immune status of NSCLC.

Challenges in Detection of Serum Oncoprotein: Relevance to Breast Cancer Diagnostics

Breast cancer is a highly prevalent malignancy that shows improved outcomes with earlier diagnosis. Current screening and monitoring methods have improved survival rates, but the limitations of these approaches have led to the investigation of biomarker evaluation to improve early diagnosis and treatment monitoring. The enzyme-linked immunosorbent assay (ELISA) is a specific and robust technique ideally suited for the quantification of protein biomarkers from blood or its constituents. The continued clinical relevancy of this assay format will require overcoming specific technical challenges, including the ultra-sensitive detection of trace biomarkers and the circumventing of potential assay interference due to the expanding use of monoclonal antibody (mAb) therapeutics. Approaches to increasing the sensitivity of ELISA have been numerous and include employing more sensitive substrates, combining ELISA with the polymerase chain reaction (PCR), and incorporating nanoparticles as shuttles for detection antibodies and enzymes. These modifications have resulted in substantial boosts in the ability to detect extremely low levels of protein biomarkers, with some systems reliably detecting antigen at sub-femtomolar concentrations. Extensive utilization of mAb therapies in oncology has presented an additional contemporary challenge for ELISA, particularly when both therapeutic and assay antibodies target the same protein antigen. Resolution of issues such as epitope overlap and steric hindrance requires a rational approach to the design of diagnostic antibodies that takes advantage of modern antibody generation pipelines, epitope binning techniques and computational methods to strategically target biomarker epitopes. This review discusses technical strategies in ELISA implemented to date and their feasibility to address current constraints on sensitivity and problems with interference in the clinical setting. The impact of these recent advancements will depend upon their transformation from research laboratory protocols into facile, reliable detection systems that can ideally be replicated in point-of-care devices to maximize utilization and transform both the diagnostic and therapeutic monitoring landscape.

Metabolic Parameters as Biomarkers of Response to Immunotherapy and Prognosis in Non-Small Cell Lung Cancer (NSCLC): A Real World Experience

Immune-checkpoint inhibitors (ICIs) have been proven to have great efficacy in non-small cell lung cancer (NSCLC) as single agents or in combination therapy, being capable to induce deep and durable remission. However, severe adverse events may occur and about 40% of patients do not benefit from the treatment. Predictive factors of response to ICIs are needed in order to customize treatment. The aim of this study is to evaluate the correlation between quantitative positron emission tomography (PET) parameters defined before starting ICI therapy and responses to treatment and patient outcome. We retrospectively analyzed 92 NSCLC patients treated with nivolumab, pembrolizumab or atezolizumab. Basal PET/computed tomography (CT) scan parameters (whole-body metabolic tumor volume-wMTV, total lesion glycolysis-wTLG, higher standardized uptake volume maximum and mean-SUVmax and SUVmean) were calculated for each patient and correlated with outcomes. Patients who achieved disease control (complete response + partial response + stable disease) had significantly lower MTV median values than patients who had not (progressive disease) (77 vs. 160.2, p = 0.039). Furthermore, patients with MTV and TLG values lower than the median values had improved OS compared to patients with higher MTV and TLG (p = 0.03 and 0.05, respectively). No relation was found between the other parameters and outcome. In conclusion, baseline metabolic tumor burden, measured with MTV, might be an independent predictor of treatment response to ICI and a prognostic biomarker in NSCLC patients.

Soluble PD-L1 in NSCLC Patients Treated with Checkpoint Inhibitors and Its Correlation with Metabolic Parameters

We investigated the role of soluble PD-L1 (sPD-L1) in non-small cell lung carcinoma (NSCLC) patients treated with immune checkpoint inhibitors (ICI) and analyzed its association with clinical outcomes and metabolic parameters by 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT). Between July 2017 and May 2019, we enrolled 20 candidate patients of ICI therapy who had serum frozen samples and 18F-FDG PET/CT available, both at baseline and at the first response evaluation. This analysis is embedded into a larger prospective study (NCT03563482). Twelve out of 20 patients received nivolumab, one patient received combination of nivolumab and ipilimumab, whereas the others received pembrolizumab. Median sPD-L1 level at baseline was 27.22 pg/mL. We found a significant association between patients with elevated sPD-L1, above the median value, and high metabolic tumor burden, expressed by metabolic tumor volume (MTV, 115.3 vs. 35.5, p = 0.034) and total lesion glycolysis (TLG, 687 vs. 210.1, p = 0.049). At the first restaging after 7–8 weeks, median sPD-L1 levels significantly increased as compared to baseline median value (43.9 pg/mL, p = 0.017). No significant differences in response rates were detected, according to both morphological and metabolic response criteria. Likewise, no difference in survival outcomes were observed between low sPD-L1 and high sPD-L1 patients. The increase of sPD-L1 concentrations during ICI treatment may reflect the expansion of tumor volume and the tumor lysis. Moreover, it is supposed that sPD-L1 has its own biological action, either by reducing membrane PD-1 sites available for nivolumab or by inducing lymphocytes exhaustion after binding their membrane PD-1. Further, larger studies are needed to confirm our preliminary results on the role of sPD-L1 during ICI therapy.

18F-FDG Pet Parameters and Radiomics Features Analysis in Advanced Nsclc Treated with Immunotherapy as Predictors of Therapy Response and Survival

Objectives: (1.1) to evaluate the association between baseline 18F-FDG PET/CT semi-quantitative parameters of the primary lesion with progression free survival (PFS), overall survival (OS) and response to immunotherapy, in advanced non-small cell lung carcinoma (NSCLC) patients eligible for immunotherapy; (1.2) to evaluate the application of radiomics analysis of the primary lesion to identify features predictive of response to immunotherapy; (1.3) to evaluate if tumor burden assessed by 18F-FDG PET/CT (N and M factors) is associated with PFS and OS. Materials and Methods: we retrospectively analyzed clinical records of advanced NCSLC patients (stage IIIb/c or stage IV) candidate to immunotherapy who performed 18F-FDG PET/CT before treatment to stage the disease. Fifty-seven (57) patients were included in the analysis (F:M 17:40; median age = 69 years old). Notably, 38/57 of patients had adenocarcinoma (AC), 10/57 squamous cell carcinoma (SCC) and 9/57 were not otherwise specified (NOS). Overall, 47.4% patients were stage IVA, 42.1% IVB and 8.8% IIIB. Immunotherapy was performed as front-line therapy in 42/57 patients and as second line therapy after chemotherapy platinum-based in 15/57. The median follow up after starting immunotherapy was 10 months (range: 1.5–68.6). Therapy response was assessed by RECIST 1.1 criteria (CT evaluation every 4 cycles of therapy) in 48/57 patients or when not feasible by clinical and laboratory data (fast disease progression or worsening of patient clinical condition in nine patients). Radiomics analysis was performed by applying regions of interest (ROIs) of the primary tumor delineated manually by two operators and semi-automatically applying a threshold at 40% of SUVmax. Results: (1.1) metabolic tumor volume (MTV) (p = 0.028) and total lesion glycolysis (TLG) (p = 0.035) were significantly associated with progressive vs. non-progressive disease status. Patients with higher values of MTV and TLG had higher probability of disease progression, compared to those patients presenting with lower values. SUVmax did not show correlation with PD status, PFS and OS. MTV (p = 0.027) and TLG (p = 0.022) also resulted in being significantly different among PR, SD and PD groups, while SUVmax was confirmed to not be associated with response to therapy (p = 0.427). (1.2) We observed the association of several radiomics features with PD status. Namely, patients with high tumor volume, TLG and heterogeneity expressed by “skewness” and “kurtosis” had a higher probability of failing immunotherapy. (1.3) M status at 18F-FDG PET/CT was significantly associated with PFS (p = 0.002) and OS (p = 0.049). No significant associations were observed for N status. Conclusions: 18F-FDG PET/CT performed before the start of immunotherapy might be an important prognostic tool able to predict the disease progression and response to immunotherapy in patients with advanced NSCLC, since MTV, TLG and radiomics features (volume and heterogeneity) are associated with disease progression.

Hyperprogressive Disease in Patients with Non-Small Cell Lung Cancer Treated with Checkpoint Inhibitors: The Role of 18F-FDG PET/CT

A new pattern of response, so-called hyperprogressive disease (HPD), is emerging during treatment with immune checkpoint inhibitors (ICIs). Our aim was to investigate the prevalence of such a phenomenon and to assess its association with clinical variables and metabolic parameters by ¹⁸F-FDG PET/CT. Methods: Data from 50 patients (34 men and 16 women; median age, 73 y) with non-small cell lung carcinoma treated with ICIs were prospectively collected. All patients underwent contrast-enhanced CT, ¹⁸F-FDG PET/CT, and complete peripheral blood sampling at baseline before ICI treatment. HPD was defined according to clinical and radiologic criteria. Because of rapid disease progression or worsening of clinical condition, radiologic response assessment was available for only 46 of the 50 patients. Overall survival (OS) was analyzed using the Kaplan-Meier method and the log-rank test. A Cox proportional hazards regression analysis was used to evaluate factors independently associated with OS. Median follow-up was 12.4 mo (range, 9.7-15.2 mo). Results: We identified the following response categories: 10 cases as complete or partial response, 17 cases as stable disease, 5 cases as progressive disease, and 14 cases as HPD. Among metabolic parameters, we observed a statistically significant association between HPD status and tumor burden, expressed by both TLG (756.1 cm³ for HPD vs. 475.6 cm³ for non-HPD, P = 0.042) and MTV (287.3 for HPD vs. 62.1 for non-HPD, P = 0.011). Among clinical variables, 12 of 14 patients (85.7%) within the HPD group, compared with 8 of 32 patients (25%) in the non-HPD group, had more than 2 metastatic sites (P < 0.001). In addition, the derived neutrophil-to-lymphocyte ratio and platelet count were significantly associated with HPD status (P = 0.038 and P = 0.025, respectively). Survival analysis showed a median OS of 4 mo for the HPD group, compared with 15 mo for the non-HPD group (P = 0.003). Likewise, median OS was significantly different when we considered all the response categories: complete or partial response, stable disease, progressive disease, and HPD (P = 0.001). Finally, multivariate analysis identified metabolic tumor volume and derived neutrophil-to-lymphocyte ratio as independent predictors for OS. Conclusion: Our results suggest that the use of ICIs might represent a concern in patients with high metabolic tumor burden and inflammatory indices at baseline. However, additional studies are needed.