Baseline metabolic tumor volume as a strong predictive and prognostic biomarker in patients with non-small cell lung cancer treated with PD1 inhibitors: a prospective study

Tumour burden and efficacy of immune-checkpoint inhibitors

Accumulating evidence suggests that a high tumour burden has a negative effect on anticancer immunity. The concept of tumour burden, simply defined as the total amount of cancer in the body, in contrast to molecular tumour burden, is often poorly understood by the wider medical community; nonetheless, a possible role exists in defining the optimal treatment strategy for many patients. Historically, tumour burden has been assessed using imaging. In particular, CT scans have been used to evaluate both the number and size of metastases as well as the number of organs involved. These methods are now often complemented by metabolic tumour burden, measured using the more recently developed 2-deoxy-2-[¹⁸F]-fluoro-D-glucose (FDG)-PET/CT. Serum-based biomarkers, such as lactate dehydrogenase, can also reflect tumour burden and are often also correlated with a poor response to immune-checkpoint inhibitors. Other circulating markers (such as circulating free tumour DNA and/or circulating tumour cells) are also attracting research interest as surrogate markers of tumour burden. In this Review, we summarize evidence supporting the utility of tumour burden as a biomarker to guide the use of immune-checkpoint inhibitors. We also describe data and provide perspective on the various tools used for tumour burden assessment, with a particular emphasis on future therapeutic strategies that might address the issue of inferior outcomes among patients with cancer with a high tumour burden.

Cancer as a Model System for Testing Metabolic Scaling Theory

Biological allometries, such as the scaling of metabolism to mass, are hypothesized to result from natural selection to maximize how vascular networks fill space yet minimize internal transport distances and resistance to blood flow. Metabolic scaling theory argues two guiding principles—conservation of fluid flow and space-filling fractal distributions—describe a diversity of biological networks and predict how the geometry of these networks influences organismal metabolism. Yet, mostly absent from past efforts are studies that directly, and independently, measure metabolic rate from respiration and vascular architecture for the same organ, organism, or tissue. Lack of these measures may lead to inconsistent results and conclusions about metabolism, growth, and allometric scaling. We present simultaneous and consistent measurements of metabolic scaling exponents from clinical images of lung cancer, serving as a first-of-its-kind test of metabolic scaling theory, and identifying potential quantitative imaging biomarkers indicative of tumor growth. We analyze data for 535 clinical PET-CT scans of patients with non-small cell lung carcinoma to establish the presence of metabolic scaling between tumor metabolism and tumor volume. Furthermore, we use computer vision and mathematical modeling to examine predictions of metabolic scaling based on the branching geometry of the tumor-supplying blood vessel networks in a subset of 56 patients diagnosed with stage II-IV lung cancer. Examination of the scaling of maximum standard uptake value with metabolic tumor volume, and metabolic tumor volume with gross tumor volume, yield metabolic scaling exponents of 0.64 (0.20) and 0.70 (0.17), respectively. We compare these to the value of 0.85 (0.06) derived from the geometric scaling of the tumor-supplying vasculature. These results: (1) inform energetic models of growth and development for tumor forecasting; (2) identify imaging biomarkers in vascular geometry related to blood volume and flow; and (3) highlight unique opportunities to develop and test the metabolic scaling theory of ecology in tumors transitioning from avascular to vascular geometries.

Whole-body PET Imaging of T-cell Response to Glioblastoma

PURPOSE

Immunotherapy is a promising approach for many oncological malignancies, including glioblastoma, however, there are currently no available tools or biomarkers to accurately assess whole-body immune responses in patients with glioblastoma treated with immunotherapy. Here, the utility of OX40, a costimulatory molecule mainly expressed on activated effector T cells known to play an important role in eliminating cancer cells, was evaluated as a PET imaging biomarker to quantify and track response to immunotherapy.

EXPERIMENTAL DESIGN

A subcutaneous vaccination approach of CpG oligodeoxynucleotide, OX40 mAb, and tumor lysate at a remote site in a murine orthotopic glioma model was developed to induce activation of T cells distantly while monitoring their distribution in stimulated lymphoid organs with respect to observed therapeutic effects. To detect OX40-positive T cells, we utilized our in-house-developed ⁸⁹Zr-DFO-OX40 mAb and in vivo PET/CT imaging.

RESULTS

ImmunoPET with ⁸⁹Zr-DFO-OX40 mAb revealed strong OX40-positive responses with high specificity, not only in the nearest lymph node from vaccinated area (mean, 20.8%ID/cc) but also in the spleen (16.7%ID/cc) and the tumor draining lymph node (11.4%ID/cc). When the tumor was small (<10⁶ p/sec/cm²/sr in bioluminescence imaging), a high number of responders and percentage shrinkage in tumor signal was indicated after only a single cycle of vaccination.

CONCLUSIONS

The results highlight the promise of clinically translating cancer vaccination as a potential glioma therapy, as well as the benefits of monitoring efficacy of these treatments using immunoPET imaging of T-cell activation.

Immune Checkpoint Inhibitors in Advanced NSCLC: [18F]FDG PET/CT as a Troubleshooter in Treatment Response

Introduction: The aim of this study was to investigate whether [¹⁸F]FDG PET/CT-derived semi-quantitative parameters can predict immunotherapy treatment response in non-small cell lung cancer (NSCLC) patients. Secondly, immune-related adverse events (irAEs) and lymphoid cell-rich organs activation were evaluated. Materials and Methods: Twenty-eight patients who underwent [¹⁸F]FDG PET/CT scans before and at first restaging therapy with immuno-checkpoint inhibitors (ICIs) were retrospectively analyzed. PET-based semi-quantitative parameters extracted from both scans were respectively: SUV_max and SUV_peak of the target lesion, whole-body metabolic tumor volume (MTV_WB), and whole-body total lesion glycolysis (TLG_WB), as well as their interval changes (ΔSUV_maxTL, ΔSUV_peakTL, ΔMTV_WB, ΔTLG_WB). These PET-derived parameters were correlated to controlled disease (CD) assessed by RECIST 1.1. IrAEs, if present, were also described and correlated with clinical benefit (CB). SUV_max of the spleen and bone marrow at restaging scans were also correlated to CB. Results: The CD was achieved in 54% of patients. Out of 28 eligible patients, 13 (46%) experienced progressive disease (PD), 7 showed SD, 7 had PR, and only in one patient CR was achieved. ΔSUV_maxTL (p = 0.002) and ΔSUV_peakTL (p < 0.001) as well as ΔMTV_WB (p < 0.001) and ΔTLG_WB (p < 0.005) were significantly associated with PD vs. non-PD. IrAEs and lymphoid cell-rich organs activation did not correlate with CB. Conclusions: [¹⁸F]FDG PET/CT by using interval changes of PET-derived semi-quantitative parameters could represent a reliable tool in immunotherapy treatment response evaluation in NSCLC patients.

Molecular Imaging and the PD-L1 Pathway: From Bench to Clinic

Programmed death-1 (PD-1) and programmed death ligand 1 (PD-L1) inhibitors target the important molecular interplay between PD-1 and PD-L1, a key pathway contributing to immune evasion in the tumor microenvironment (TME). Long-term clinical benefit has been observed in patients receiving PD-(L)1 inhibitors, alone and in combination with other treatments, across multiple tumor types. PD-L1 expression has been associated with response to immune checkpoint inhibitors, and treatment strategies are often guided by immunohistochemistry-based diagnostic tests assessing expression of PD-L1. However, challenges related to the implementation, interpretation, and clinical utility of PD-L1 diagnostic tests have led to an increasing number of preclinical and clinical studies exploring interrogation of the TME by real-time imaging of PD-(L)1 expression by positron emission tomography (PET). PET imaging utilizes radiolabeled molecules to non-invasively assess PD-(L)1 expression spatially and temporally. Several PD-(L)1 PET tracers have been tested in preclinical and clinical studies, with clinical trials in progress to assess their use in a number of cancer types. This review will showcase the development of PD-(L)1 PET tracers from preclinical studies through to clinical use, and will explore the opportunities in drug development and possible future clinical implementation.

Tumor burden as possible biomarker of outcome in advanced NSCLC patients treated with immunotherapy: a single center, retrospective, real-world analysis

AIM

The role of tumor burden (TB) for patients with non-small cell lung cancer (NSCLC) receiving immunotherapy is still unknown. The aim of this analysis was to analyze the prognostic value of TB in a real-world sample of advanced NSCLC patients.

METHODS

Sixty-five consecutive patients with advanced NSCLC treated with immunotherapy as first or second line therapy were retrospectively analyzed between August 2015 and February 2018. TB was recorded at baseline considering sites and number of metastases, thoracic vs. extrathoracic disease, measurable disease (MD) vs. not-MD (NMD) and evaluating dimensional aspects as maximum lesion diameter (cut-off = 6.3 cm), sum of the 5 major lesions diameters (cut-off = 14.3 cm), and number of sites of metastases (cut-off > 4). All cut-offs were calculated by receiver operating characteristic curves. Median overall survival (OS) was estimated using Kaplan-Meier method. A Cox regression model was carried out for univariate and multivariate analyses.

RESULTS

Median age was 70 years and most patients (86.2%) had a good performance status (PS-Eastern Cooperative Oncology Group < 2). No significant difference in OS was noted between subgroups of patients according to TB. Bone metastases (BM) had a negative prognostic impact [median OS (mOS), 13.8 vs. 70.0 months, P = 0.0009; median progression free survival in the second line (mPFS2) 2.97 vs. 8.63 months; P = 0.0037]. Patients with NMD had a poorer prognosis (mOS, 15.9 months vs. not reached, P < 0.0001; mPFS2 3.8 vs. 12.2 months; P = 0.0199). Patients with disease limited to the thorax had a better prognosis compared to patients with involvement of extrathoracic sites (mOS, 70 vs. 17.3 months; P = 0.0136). Having more than 4 metastatic sites resulted as a negative prognostic factor (mOS, 15.9 vs. 25.2 months; P = 0.0106). At multivariate analysis, BM, NMD, extrathoracic disease and number of sites of metastases > 4 were negative prognostic factors (P < 0.0001).

CONCLUSIONS

This study underlines the negative prognostic impact of specific metastatic sites, presence of NMD and extrathoracic disease in advanced NSCLC patients treated with immunotherapy. However, TB does not appear to affect the outcome of these patients.

Combination of radiation therapy, bempegaldesleukin, and checkpoint blockade eradicates advanced solid tumors and metastases in mice

Background

Current clinical trials are using radiation therapy (RT) to enhance an antitumor response elicited by high-dose interleukin (IL)-2 therapy or immune checkpoint blockade (ICB). Bempegaldesleukin (BEMPEG) is an investigational CD122-preferential IL-2 pathway agonist with prolonged in vivo half-life and preferential intratumoral expansion of T effector cells over T regulatory cells. BEMPEG has shown encouraging safety and efficacy in clinical trials when used in combination with PD-1 checkpoint blockade. In this study, we investigated the antitumor effect of local RT combined with BEMPEG in multiple immunologically ‘cold’ tumor models. Additionally, we asked if ICB could further enhance the local and distant antitumor effect of RT+BEMPEG in the setting of advanced solid tumors or metastatic disease.

Methods

Mice bearing flank tumors (B78 melanoma, 4T1 breast cancer, or MOC2 head and neck squamous cell carcinoma) were treated with combinations of RT and immunotherapy (including BEMPEG, high-dose IL-2, anti(α)-CTLA-4, and α-PD-L1). Mice bearing B78 flank tumors were injected intravenously with B16 melanoma cells to mimic metastatic disease and were subsequently treated with RT and/or immunotherapy. Tumor growth and survival were monitored. Peripheral T cells and tumor-infiltrating lymphocytes were assessed via flow cytometry.

Results

A cooperative antitumor effect was observed in all models when RT was combined with BEMPEG, and RT increased IL-2 receptor expression on peripheral T cells. This cooperative interaction was associated with increased IL-2 receptor expression on peripheral T cells following RT. In the B78 melanoma model, RT+BEMPEG resulted in complete tumor regression in the majority of mice with a single ~400 mm³ tumor. This antitumor response was T-cell dependent and supported by long-lasting immune memory. Adding ICB to RT+BEMPEG strengthened the antitumor response and cured the majority of mice with a single ~1000 mm³ B78 tumor. In models with disseminated metastasis (B78 primary with B16 metastasis, 4T1, and MOC2), the triple combination of RT, BEMPEG, and ICB significantly improved primary tumor response and survival.

Conclusion

The combination of local RT, BEMPEG, and ICB cured mice with advanced, immunologically cold tumors and distant metastasis in a T cell-dependent manner, suggesting this triple combination warrants clinical testing.

Long-Term Follow-Up of Mesothelioma Patients Treated with Dendritic Cell Therapy in Three Phase I/II Trials

Background: Malignant pleural mesothelioma (MPM) is a fatal neoplasm with, if untreated, poor survival of approximately nine months from diagnosis. Until recently, phase II–III immunotherapy trials did not show any significant benefit. The lack of immunotherapy efficacy can be explained by the fact that mesothelioma is a tumor with an “immune desert” phenotype, meaning a non-inflamed tumor characterized by low T-cell infiltration. By administration of DCs, which were ex-vivo cultured, exposed to (tumor-associated) antigens, and subsequently activated, this “immune desert” phenotype might be turned into an “inflamed” phenotype. Three phase I/II studies have been performed and published using activated DCs, which support this concept. We here report on the long-term survival of patients treated with DCs in three phase I/II studies. Methods: Survival data of the phase I/II trials using DC therapy in MPM patients were obtained and subsequently analyzed. In the first two trials, DCs were loaded with autologous tumor lysate. In the third trial, DCs were loaded with allogeneic mesothelioma tumor cell line lysate. Results: In the three studies combined, 29 patients with MPM were treated with DC vaccination between 2006 and 2015. At data cut-off, the median OS was 27 months (95% CI: 21–47 months). OS at 2 years was 55.2% (95% CI: 39.7–76.6%), and OS at 5 years was 20.7% (95% CI: 10.1–42.2%). Conclusions: The long-term survival of DC therapy in MPM in these three trials is promising, which is the basis for the randomized phase II/III DENIM study. This DENIM study is currently enrolling, and the results of which have to be awaited for definite conclusions.

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.

Three-Dimensional Deep Noninvasive Radiomics for the Prediction of Disease Control in Patients With Metastatic Urothelial Carcinoma treated With Immunotherapy

INTRODUCTION

Immunotherapy is effective in a small percentage of patients with cancer and no reliable predictive biomarkers are currently available. Artificial Intelligence algorithms may automatically quantify radiologic characteristics associated with disease response to medical treatments.

METHODS

We investigated an innovative approach based on a 3-dimensional (3D) deep radiomics pipeline to classify visual features of chest-abdomen computed tomography (CT) scans with the aim of distinguishing disease control from progressive disease to immune checkpoint inhibitors (ICIs). Forty-two consecutive patients with metastatic urothelial cancer had progressed on first-line platinum-based chemotherapy and had baseline CT scans at immunotherapy initiation. The 3D-pipeline included self-learned visual features and a deep self-attention mechanism. According to the outcome to the ICIs, a 3D deep classifier semiautomatically categorized the most discriminative region of interest on the CT scans.

RESULTS

With a median follow-up of 13.3 months (95% CI, 11.1-15.6), the median overall survival was 8.5 months (95% CI, 3.1-13.8). According to disease response to immunotherapy, the median overall survival was 3.6 months (95% CI, 2.0-5.2) for patients with progressive disease; it was not yet reached for those with disease control. The predictive accuracy of the 3D-pipeline was 82.5% (sensitivity 96%; specificity, 60%). The addition of baseline clinical factors increased the accuracy to 92.5% by improving specificity to 87%; the accuracy of other architectures ranged from 72.5% to 90%.

CONCLUSION

Artificial Intelligence by 3D deep radiomics is a potential noninvasive biomarker for the prediction of disease control to ICIs in metastatic urothelial cancer and deserves validation in larger series.

Identification of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma Based on Multi-Omics Analysis

We aimed to explore the tumor mutational burden (TMB) and immune infiltration in HCC and investigate new biomarkers for immunotherapy. Transcriptome and gene mutation data were downloaded from the GDC portal, including 374 HCC samples and 50 matched normal samples. Furthermore, we divided the samples into high and low TMB groups, and analyzed the differential genes between them with GO, KEGG, and GSEA. Cibersort was used to assess the immune cell infiltration in the samples. Finally, univariate and multivariate Cox regression analyses were performed to identify differential genes related to TMB and immune infiltration, and a risk prediction model was constructed. We found 10 frequently mutated genes, including TP53, TTN, CTNNB1, MUC16, ALB, PCLO, MUC, APOB, RYR2, and ABCA. Pathway analysis indicated that these TMB-related differential genes were mainly enriched in PI3K-AKT. Cibersort analysis showed that memory B cells (p = 0.02), CD8+ T cells (p = 0.09), CD4+ memory activated T cells (p = 0.07), and neutrophils (p = 0.06) demonstrated a difference in immune infiltration between high and low TMB groups. On multivariate analysis, GABRA3 (p = 0.05), CECR7 (p < 0.001), TRIM16 (p = 0.003), and IL7R (p = 0.04) were associated with TMB and immune infiltration. The risk prediction model had an area under the curve (AUC) of 0.69, suggesting that patients with low risk had better survival outcomes. Our study demonstrated for the first time that CECR7, GABRA3, IL7R, and TRIM16L were associated with TMB and promoted antitumor immunity in HCC.

Tumor Burden and Immunotherapy: Impact on Immune Infiltration and Therapeutic Outcomes

Cancer immunotherapy has revolutionized the treatment landscape in medical oncology, but its efficacy has been variable across patients. Biomarkers to predict such differential response to immunotherapy include cytotoxic T lymphocyte infiltration, tumor mutational burden, and microsatellite instability. A growing number of studies also suggest that baseline tumor burden, or tumor size, predicts response to immunotherapy. In this review, we discuss the changes in immune profile and therapeutic responses that occur with increasing tumor size. We also overview therapeutic approaches to reduce tumor burden and favorably modulate the immune microenvironment of larger tumors.