iRECIST and atypical patterns of response to immuno-oncology drugs

A landscape of checkpoint blockade resistance in cancer: underlying mechanisms and current strategies to overcome resistance

The discovery of immune checkpoints and the development of immune checkpoint inhibitors (ICI) have achieved a durable response in advanced-stage cancer patients. However, there is still a high proportion of patients who do not benefit from ICI therapy due to a lack of response when first treated (primary resistance) or detection of disease progression months after objective response is observed (acquired resistance). Here, we review the current FDA-approved ICI for the treatment of certain solid malignancies, evaluate the contrasting responses to checkpoint blockade in different cancer types, explore the known mechanisms associated with checkpoint blockade resistance (CBR), and assess current strategies in the field that seek to overcome these mechanisms. In order to improve current therapies and develop new ones, the immunotherapy field still has an unmet need in identifying other molecules that act as immune checkpoints, and uncovering other mechanisms that promote CBR.

Immune-Related Adverse Events Can Predict Progression-Free and Overall Survival In Patients With Metastatic Renal Cell Carcinoma Treated With Immune Checkpoint Inhibitors

BACKGROUND

Different combination therapies using anti - PD-1 / PD-L1 or CTLA-4 immune checkpoint inhibition (ICI) are widely used in patients with metastatic renal cell carcinoma (mRCC). In the absents of established biomarkers, immune-related adverse events (irAEs) have been discussed as potential predictors of response.

METHODS

In this retrospective cohort study, data of 134 patients with mRCC undergoing ICI treatment (Nivolumab, Ipilimumab and Nivolumab, Pembrolizumab and Axitinib or Avelumab and Axitinib) between 2015 and 2021 were analyzed. To examine the utility of irAEs as predictors of overall survival (OS) and progression-free survival (PFS), separate Kaplan-Meier analyses and Cox proportional regression analyses were applied. Landmark analysis was conducted after 12 weeks to reduce immortal time bias.

RESULT

irAEs were observed in 85 patients (63.4%). Cutaneous (n = 52, 38.8%), endocrine (n = 33, 24.6%) and hepatic (n = 19, 14.2%) irAEs were most commonly observed. In Kaplan-Meier analysis, patients experiencing irAEs showed favorable median PFS (15 months, 95% CI, 9.91-20.09) compared to the non-irAE group (5 months, 95% CI, 3.56-6.44, P < .001). The median OS was 25 months (95% CI, 16.79-33.21) in the non-irAE group, while it was not reached in the irAE group (P = .002). In multivariable analysis, the presence of any irAE was associated with favorable PFS (HR 0.46 [95% CI, 0.26-0.82] P = .008) and OS (HR: 0.28 [95% CI, 0.12-0.63] P = .002), respectively. Landmark analysis after 12 weeks showed mixed results depending on the classification of the irAE group at the landmark time.

CONCLUSION

The presence of irAEs under ICI therapy in patients with mRCC is associated with better PFS and OS. Thus, manageable irAEs should not be cause for premature discontinuation of ICI therapy, as they seem to indicate favorable outcomes. Considering the time-dependent nature of irAEs is crucial estimating their value as predictive markers.

Surrogate endpoints in phase III randomized trials of advanced gastroesophageal cancer: A systematic review and meta-analysis

Overall survival (OS) is the most meaningful endpoint in clinical trials. However, owing to their limitations, surrogate endpoints are commonly used and validation studies are required to assess their reliability. Analysis of phase III randomized controlled trials (RCTs) of advanced gastroesophageal cancer (AGC) with > 100 patients, correlation coefficients (r), and determination coefficients (R²) between OS and surrogates were evaluated through meta-analyses. Progression-free survival (PFS), time to progression (TTP), and objective response rate (ORR) were examined to determine their correlations with OS. Analysis of 65 phase III RCTs (29,766 subjects) showed a moderate correlation between PFS/TTP and OS (r = 0.77, R² = 0.59), while ORR correlation was low (r = 0.56, R² = 0.31). Excluding immunotherapy trials improved the PFS/TTP and OS correlations (r = 0.83, R² = 0.70). These findings suggest the potential use of PFS/TTP in AGC phase III investigations, disregarding the use of ORR as a surrogate endpoint.

The role of CD8 PET imaging in guiding cancer immunotherapy

Currently, immunotherapy is being widely used for treating cancers. However, the significant heterogeneity in patient responses is a major challenge for its successful application. CD8-positive T cells (CD8+ T cells) play a critical role in immunotherapy. Both their infiltration and functional status in tumors contribute to treatment outcomes. Therefore, accurate monitoring of CD8+ T cells, a potential biomarker, may improve therapeutic strategy. Positron emission tomography (PET) is an optimal option which can provide molecular imaging with enhanced specificity. This review summarizes the mechanism of action of CD8+ T cells in immunotherapy, and highlights the recent advancements in PET-based tracers that can visualize CD8+ T cells and discusses their clinical applications to elucidate their potential role in cancer immunotherapy.

Repeated dynamic [18F]FDG PET/CT imaging using a high-sensitivity PET/CT scanner for assessing non-small cell lung cancer patients undergoing induction immuno-chemotherapy followed by hypo-fractionated chemoradiotherapy and consolidative immunotherapy: report from a prospective observational study (GASTO-1067)

OBJECTIVE

The study aims to investigate the role of dynamic [18F]FDG PET/CT imaging by high-sensitivity PET/CT scanner for assessing patients with locally advanced non-small cell lung cancer (LA-NSCLC) who undergo induction immuno-chemotherapy, followed by concurrent hypo-fractionated chemoradiotherapy (hypo-CCRT) and consolidative immunotherapy.

METHODS

Patients with unresectable LA-NSCLC are prospectively recruited. Dynamic [18F]FDG PET/CT scans are conducted at four timepoints: before treatment (Baseline), after induction immuno-chemotherapy (Post-IC), during hypo-CCRT (Mid-hypo-CCRT) and after hypo-CCRT (Post-hypo-CCRT). The primary lung tumors (PTs) are manually delineated, and the metabolic features, including the Patlak-Ki (Ki), maximum SUV (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have been evaluated. The expressions of CD3, CD8, CD68, CD163, CD34 and Ki67 in primary lung tumors at baseline are assayed by immunohistochemistry. The levels of blood lymphocytes at four timepoints are analyzed with flow cytometry.

RESULTS

Fifteen LA-NSCLC patients are enrolled between December 2020 and December 2022. Baseline Ki of primary tumor yields the highest AUC values of 0.722 and 0.796 for predicting disease progression and patient death, respectively. Patients are classified into the High FDG Ki group (n = 8, Ki > 2.779 ml/min/100 g) and the Low FDG Ki group (n = 7, Ki ≤ 2.779 ml/min/100 g). The High FDG Ki group presents better progression-free survival (P = 0.01) and overall survival (P = 0.025). The High FDG Ki group exhibits more significant reductions in Ki after hypo-CCRT compared to the Low FDG Ki group. Patients with a reduction in Ki > 73.1% exhibit better progression-free survival than those with a reduction ≤ 73.1% in Ki (median: not reached vs. 7.33 months, P = 0.12). The levels of CD3+ T cells (P = 0.003), CD8+ T cells (P = 0.002), CD68+ macrophages (P = 0.071) and CD163+ macrophages (P = 0.012) in primary tumor tissues are higher in the High FDG Ki group. The High FDG Ki group has higher CD3+CD8+ lymphocytes in blood at baseline (P = 0.108), post-IC (P = 0.023) and post-hypo-CCRT (P = 0.041) than the Low FDG Ki group.

CONCLUSIONS

The metabolic features in the High FDG Ki group significantly decrease during the treatment, particularly after induction immuno-chemotherapy. The Ki value of primary tumor shows significant relationship with the treatment response and survival in LA-NSCLC patients by the combined immuno-chemoradiotherapy regimen.

TRIAL REGISTRATION

ClinicalTrials.gov. NCT04654234. Registered 4 December 2020.

On-treatment Modified Glasgow Prognostic Score Provides Predictive Information Complementary to Radiological Staging in Metastatic Urothelial Carcinoma on Immunotherapy

In the immunotherapy era it is difficult to predict patient prognosis on the basis of radiological staging alone, especially for the subgroup with stable disease (SD), which encompasses a wide range of clinical outcomes. Thus, there is need for reliable and, ideally, cost-efficient biomarkers to improve the accuracy of outcome prediction. We evaluated the on-treatment modified Glasgow Prognostic Score (mGPS)-a known predictor of outcomes in several cancers that is based on serum C-reactive protein and albumin-in patients with metastatic urothelial carcinoma (mUC) treated with immune checkpoint inhibition (ICI) in the phase 2 IMvigor210 and phase 3 IMvigor211 trials. On-treatment mGPS provides valuable prognostic information complementary to radiological staging, particularly for patients with SD. In IMvigor210, on-treatment mGPS predicts outcomes as early as 6 wk after ICI initiation, considerably before the first routine staging typically performed after 10-12 wk. Our study suggests that on-treatment mGPS complements radiological imaging in predicting outcomes for patients with mUC undergoing ICI. PATIENT SUMMARY: For patients with metastatic bladder cancer receiving immunotherapy, it is difficult to predict treatment outcomes from imaging scans alone. Our study results suggest that a score called the modified Glasgow Prognostic Score based on just two proteins (C-reactive protein and albumin) measured in blood can accurately predict outcomes. Use of the mGPS along with imaging scans may be better in predicting the survival benefit from immunotherapy.

Integration of on-treatment modified Glasgow prognostic score (mGPS) to improve imaging-based prediction of outcomes in patients with non-small cell lung cancer on immune checkpoint inhibition

INTRODUCTION

A large number of patients with non-small cell lung cancer (NSCLC) on immune checkpoint inhibition (ICI) achieve stable disease (SD) as the best overall response, which is associated with heterogeneous outcomes. In this context, complementary biomarkers that improve outcome prediction are needed. We have recently demonstrated that measuring the on-treatment modified Glasgow prognostic score (mGPS), which is based on the two serum markers C-reactive protein (CRP) and albumin, can improve outcome prediction complementary to radiological staging in metastatic renal cell carcinoma. However, this concept has not been assessed for patients with NSCLC on ICI.

METHODS

We assessed the prognostic and predictive value of on-treatment mGPS at week six in patients with NSCLC treated with atezolizumab or docetaxel in the phase 3 OAK trial (NCT02008227) comprising n = 750 patients and validated the findings in the phase 2 BIRCH (NCT02031458, n = 560).

RESULTS

On-treatment mGPS assessed at week six demonstrated valuable prognostic information (Hazard Ratio (HR) for mGPS low-risk vs intermediate risk 2.34 (95 % CI 1.76-3.11, p < 0.001) and vs high risk 3.56, (95 % CI 2.57-4.91, p < 0.001) in the atezolizumab-treated subgroup. On-treatment mGPS predicted overall survival more accurately than imaging using RECIST criteria (concordance index: on-treatment mGPS 0.646 (95 % CI 0.615-0.677) vs RECIST 0.606 (95 % CI 0.575-0.637)). On-treatment mGPS provides additional prognostic information to imaging-assessed treatment response at first staging, especially for the patient subgroup with SD. These findings were validated in the BIRCH trial.

CONCLUSIONS

We highlight the novel concept of integrating on-treatment mGPS for improved outcome prediction in conjunction with radiological imaging for patients with NSCLC on ICI.

Tumor Response Evaluation Using iRECIST: Feasibility and Reliability of Manual Versus Software-Assisted Assessments

OBJECTIVES

To compare the feasibility and reliability of manual versus software-assisted assessments of computed tomography scans according to iRECIST in patients undergoing immune-based cancer treatment.

METHODS

Computed tomography scans of 30 tumor patients undergoing cancer treatment were evaluated by four independent radiologists at baseline (BL) and two follow-ups (FU), resulting in a total of 360 tumor assessments (120 each at BL/FU1/FU2). After image interpretation, tumor burden and response status were either calculated manually or semi-automatically as defined by software, respectively. The reading time, calculated sum of longest diameter (SLD), and tumor response (e.g., "iStable Disease") were determined for each assessment. After complete data collection, a consensus reading among the four readers was performed to establish a reference standard for the correct response assignments. The reading times, error rates, and inter-reader agreement on SLDs were statistically compared between the manual versus software-assisted approaches.

RESULTS

The reading time was significantly longer for the manual versus software-assisted assessments at both follow-ups (median [interquartile range] FU1: 4.00 min [2.17 min] vs. 2.50 min [1.00 min]; FU2: 3.75 min [1.88 min] vs. 2.00 min [1.50 min]; both p < 0.001). Regarding reliability, 2.5% of all the response assessments were incorrect at FU1 (3.3% manual; 0% software-assisted), which increased to 5.8% at FU2 (10% manual; 1.7% software-assisted), demonstrating higher error rates for manual readings. Quantitative SLD inter-reader agreement was inferior for the manual compared to the software-assisted assessments at both FUs (FU1: ICC = 0.91 vs. 0.93; FU2: ICC = 0.75 vs. 0.86).

CONCLUSIONS

Software-assisted assessments may facilitate the iRECIST response evaluation of cancer patients in clinical routine by decreasing the reading time and reducing response misclassifications.

Considerations for the clinical development of immuno-oncology agents in cancer

Targeting of the immune system has shown to be a successful therapeutic approach in cancer, with the development of check point inhibitors (ICI) or T-cell engagers (TCE). As immuno-oncology agents modulate the immune system to attack cancer cells and do not act directly on oncogenic vulnerabilities, specific characteristics of these compounds should be taken in consideration during clinical development. In this review we will discuss relevant concepts including limitations of preclinical models, special pharmacologic boundaries, clinical development strategies such as the selection of clinical indication, line of treatment and backbone partner, as well as the endpoints and expected magnitude of benefit required at different stages of the drug development. In addition, future directions for early and late trial designs will be reviewed. Examples from approved drugs or those currently in clinical development will be discussed and options to overcome these limitations will be provided.

Pembrolizumab alone and pembrolizumab plus chemotherapy in previously treated, extrapulmonary poorly differentiated neuroendocrine carcinomas

BACKGROUND

To date, single-agent immune checkpoint inhibitor (CPI) therapy has proven to be ineffective against biomarker-unselected extrapulmonary poorly differentiated neuroendocrine carcinomas (EP-PDNECs). The efficacy of CPI in combination with chemotherapy remains under investigation.

METHODS

Patients with advanced, progressive EP-PDNECs were enrolled in a two-part study of pembrolizumab-based therapy. In Part A, patients received pembrolizumab alone. In Part B, patients received pembrolizumab plus chemotherapy.

PRIMARY ENDPOINT

objective response rate (ORR). Secondary endpoints: safety, progression-free survival (PFS) and overall survival (OS). Tumours were profiled for programmed death-ligand 1 expression, microsatellite-high/mismatch repair deficient status, mutational burden (TMB), genomic correlates. Tumour growth rate was evaluated.

RESULTS

Part A (N = 14): ORR (pembrolizumab alone) 7% (95% CI, 0.2-33.9%), median PFS 1.8 months (95% CI, 1.7-21.4), median OS 7.8 months (95% CI, 3.1-not reached); 14% of patients (N = 2) had grade 3/4 treatment-related adverse events (TRAEs). Part B (N = 22): ORR (pembrolizumab plus chemotherapy) 5% (95% CI, 0-22.8%), median PFS 2.0 months (95% CI, 1.9-3.4), median OS 4.8 months (95% CI, 4.1-8.2); 45% of patients (N = 10) had grade 3/4 TRAEs. The two patients with objective response had high-TMB tumours.

DISCUSSION

Treatment with pembrolizumab alone and pembrolizumab plus chemotherapy was ineffective in advanced, progressive EP-PDNECs.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT03136055.

Immune checkpoint inhibitors in hepatocellular carcinoma: emerging challenges in clinical practice

Systemic therapy for advanced hepatocellular carcinoma has expanded at an unprecedented pace over the past 5 years. After tyrosine kinase inhibitors dominated the field for more than a decade, immune checkpoint inhibitor (ICI)-based therapies have become the main component in systemic first-line treatment of this cancer. Delivery of immunotherapy in routine clinical practice recognises several challenges. In this Viewpoint, we discuss the major gaps in knowledge around the role of ICI-based therapies in patients with Child-Pugh class B. We discuss the challenges in individuals with rare histological subtypes of primary liver cancer, including combined hepatocellular-cholangiocarcinoma, fibrolamellar hepatocellular carcinoma, and sarcomatoid hepatocellular carcinoma. We also review data on ICI rechallenge in patients previously treated with ICIs, and discuss atypical patterns of progression related to immunotherapy (ie, hyperprogressive disease and pseudoprogression).

Lack of Influence of Non-Overlapping Mutations in BRAF, NRAS, or NF1 on 12-Month Best Objective Response and Long-Term Survival after Checkpoint Inhibitor-Based Treatment for Metastatic Melanoma

BACKGROUND

Non-overlapping somatic mutations in BRAF, NRAS, or NF1 genes occur in 85% of metastatic melanoma patients. It is not known whether these mutations affect immunotherapy outcome.

MATERIALS AND METHODS

Next-Gen sequencing of 324 oncogenes was performed in 73 metastatic melanoma patients. A retrospective review of immunotherapy outcome was performed.

RESULTS

BRAF fusions/internal rearrangements, BRAF V600E, NRAS, NF1 mutations, and triple-negative genotypes occurred in 6.9%, 30.1%, 17.8%, 32.9%, and 12.3% of patients, respectively. Median potential follow-up was 41.0 months. Patients with BRAF fusion/rearrangement had decreased progression-free and overall survival (p = 0.015). The other genotypes each had similar progression-free and overall survival. Patients who achieved a complete best objective response at 12 months (n = 36, 49.3%) were found to have significantly improved survival compared those who failed to achieve remissions (n = 37, 50.7%, p < 0.001).

CONCLUSIONS

The most important determinant of long-term survival was achievement of a complete response by 12 months following immunotherapy. PR and SD were not a stable type of response and generally resulted in progression and death from melanoma. Rare patients with BRAF fusions or rearrangements had decreased progression-free and overall survival following initial immunotherapy. Other BRAF, NRAS, or NF1 mutations were not associated with significant differences in outcome.

Translating Data Science Results into Precision Oncology Decisions: A Mini Review

While reviewing and discussing the potential of data science in oncology, we emphasize medical imaging and radiomics as the leading contextual frameworks to measure the impacts of Artificial Intelligence (AI) and Machine Learning (ML) developments. We envision some domains and research directions in which radiomics should become more significant in view of current barriers and limitations.

Automatic Classification of Tumor Response From Radiology Reports With Rule-Based Natural Language Processing Integrated Into the Clinical Oncology Workflow

PURPOSE

Imaging reports in oncology provide critical information about the disease evolution that should be timely shared to tailor the clinical decision making and care coordination of patients with advanced cancer. However, tumor response stays unstructured in free-text and underexploited. Natural language processing (NLP) methods can help provide this critical information into the electronic health records (EHR) in real time to assist health care workers.

METHODS

A rule-based algorithm was developed using SAS tools to automatically extract and categorize tumor response within progression or no progression categories. 2,970 magnetic resonance imaging, computed tomography scan, and positron emission tomography French reports were extracted from the EHR of a large comprehensive cancer center to build a 2,637-document training set and a 603-document validation set. The model was also tested on 189 imaging reports from 46 different radiology centers. A tumor dashboard was created in the EHR using the Timeline tool of the vis.js javascript library.

RESULTS

An NLP methodology was applied to create an ontology of radiographic terms defining tumor response, mapping text to five main concepts, and application decision rules on the basis of clinical practice RECIST guidelines. The model achieved an overall accuracy of 0.88 (ranging from 0.87 to 0.94), with similar performance on both progression and no progression classification. The overall accuracy was 0.82 on reports from different radiology centers. Data were visualized and organized in a dynamic tumor response timeline. This tool was deployed successfully at our institution both retrospectively and prospectively as part of an automatic pipeline to screen reports and classify tumor response in real time for all metastatic patients.

CONCLUSION

Our approach provides an NLP-based framework to structure and classify tumor response from the EHR and integrate tumor response classification into the clinical oncology workflow.

Imaging endpoints for clinical trial use: a RECIST perspective

Twenty years after its initial introduction, Response Evaluation Criteria in Solid Tumors (RECIST) remains today a unique standardized tool allowing uniform objective evaluation of response in solid tumors in clinical trials across different treatment indications. Several attempts have been made to update or replace RECIST, but none have realized the general traction or uptake seen with RECIST. This communication provides an overview of some challenges faced by RECIST in the rapidly changing oncology landscape, including the incorporation of PET with ¹⁸F-fluorodeoxyglucose tracer as a tool for response assessment and the validation of criteria for use in trials involving immunotherapeutics. The latter has mainly been slow due to lack of data sharing. Work is ongoing to try to address this.We also aim to share our view as statistician representatives on the RECIST Working Group on what would be needed to validate new imaging endpoints for clinical trial use, with a specific focus on RECIST. Whether this could lead to an update of RECIST or replace RECIST altogether, depends on the changes being proposed. The ultimate goal remains to have a well defined, repeatable, confirmable and objective standard as provided by RECIST today.