RECIST 1.1 for Response Evaluation Apply Not Only to Chemotherapy-Treated Patients But Also to Targeted Cancer Agents: A Pooled Database Analysis

Mixed responses to targeted therapy driven by chromosomal instability through p53 dysfunction and genome doubling

The phenomenon of mixed/heterogenous treatment responses to cancer therapies within an individual patient presents a challenging clinical scenario. Furthermore, the molecular basis of mixed intra-patient tumor responses remains unclear. Here, we show that patients with metastatic lung adenocarcinoma harbouring co-mutations of EGFR and TP53, are more likely to have mixed intra-patient tumor responses to EGFR tyrosine kinase inhibition (TKI), compared to those with an EGFR mutation alone. The combined presence of whole genome doubling (WGD) and TP53 co-mutations leads to increased genome instability and genomic copy number aberrations in genes implicated in EGFR TKI resistance. Using mouse models and an in vitro isogenic p53-mutant model system, we provide evidence that WGD provides diverse routes to drug resistance by increasing the probability of acquiring copy-number gains or losses relative to non-WGD cells. These data provide a molecular basis for mixed tumor responses to targeted therapy, within an individual patient, with implications for therapeutic strategies.

Anti-PD-(L)1 plus BRAF/MEK inhibitors (triplet therapy) after failure of immune checkpoint inhibition and targeted therapy in patients with advanced melanoma

BACKGROUND

Effective treatment options are limited for patients with advanced melanoma who have progressed on immune checkpoint inhibitors (ICI) and targeted therapies (TT). Preclinical models support the combination of ICI with TT; however, clinical trials evaluating the efficacy of triplet combinations in first-line setting showed limited advantage compared to TT only.

METHODS

We conducted a retrospective, multicenter study, that included patients with advanced melanoma who were treated with BRAF/MEK inhibitors in combination with an anti-PD-(L)1 antibody (triplet therapy) after failure of at least one anti-PD-(L)1-based therapy and one TT in seven major melanoma centers between February 2016 and July 2022.

RESULTS

A total of 48 patients were included, of which 32 patients, 66.7% had brain metastases, 37 patients (77.1%) had three or more metastatic organs and 21 patients (43.8%) had three or more treatment lines. The median follow-up time was 31.4 months (IQR, 22.27-40.45 months). The treatment with triplet therapy resulted in an ORR of 35.4% (n = 17) and a DCR of 47.9% (n = 23). The median DOR was 5.9 months (range, 3.39-14.27 months). Patients treated with BRAF/MEK inhibitors as the last treatment line showed a slightly lower ORR (29.6%) compared to patients who received ICI or chemotherapy last (ORR: 42.9%). Grade 3-4 treatment-related adverse events occurred in 25% of patients (n = 12), with seven patients (14.6%) requiring discontinuation of treatment with both or either drug.

CONCLUSIONS

Triplet therapy has shown activity in heavily pretreated patients with advanced melanoma and may represent a potential treatment regimen after failure of ICI and TT.

Tumor Size Is Not Everything: Advancing Radiomics as a Precision Medicine Biomarker in Oncology Drug Development and Clinical Care. A Report of a Multidisciplinary Workshop Coordinated by the RECIST Working Group

Radiomics, the science of extracting quantifiable data from routine medical images, is a powerful tool that has many potential applications in oncology. The Response Evaluation Criteria in Solid Tumors Working Group (RWG) held a workshop in May 2022, which brought together various stakeholders to discuss the potential role of radiomics in oncology drug development and clinical trials, particularly with respect to response assessment. This article summarizes the results of that workshop, reviewing radiomics for the practicing oncologist and highlighting the work that needs to be done to move forward the incorporation of radiomics into clinical trials.

Circulating tumor DNA validity and potential uses in metastatic breast cancer

Following the first characterization of circulating tumor DNA (ctDNA) in the 1990s, recent advances led to its introduction in the clinics. At present, the European Society Of Medical Oncology (ESMO) recommendations endorse ctDNA testing in routine clinical practice for tumor genotyping to direct molecularly targeted therapies in patients with metastatic cancer. In studies on metastatic breast cancer, ctDNA has been utilized for treatment tailoring, tracking mechanisms of drug resistance, and for predicting disease response before imaging. We review the available evidence regarding ctDNA applications in metastatic breast cancer.

Liquid Biopsy Response Evaluation Criteria in Solid Tumors (LB-RECIST)

Current evaluation of treatment response in solid tumors depends on dynamic changes in tumor diameters as measured by imaging. However, these changes can only be detected when there are enough macroscopic changes in tumor volume, which limits the usability of radiological response criteria in evaluating earlier stages of disease response and necessitates much time to lapse for gross changes to be notable. One promising approach is to incorporate dynamic changes in circulating tumor DNA (ctDNA), which occur early in the course of therapy and can predict tumor responses weeks before gross size changes manifest. However, several issues need to be addressed before recommending the implementation of ctDNA response criteria in daily clinical practice such as clinical, biological, and regulatory challenges and, most importantly, the need to standardize/harmonize detection methods and ways to define ctDNA response and/or progression for precision oncology. Herein, we review the use of liquid biopsy (LB) to evaluate response in solid tumors and propose a plan toward standardization of LB-RECIST.

Heterogeneity of Radiological Progression Patterns and Association with Outcomes in Patients with Metastatic Prostate Cancer

BACKGROUND

With an increasing number of clinical trials using radiographic progression-free survival (rPFS) instead of overall survival as the primary study endpoint, the heterogeneity of different radiological progression patterns in rPFS and postprogression survival (PPS) remains unclear.

OBJECTIVE

Herein, we investigate the proportion of various radiological progression patterns in patients with metastatic hormone-sensitive prostate cancer (mHSPC) and metastatic castration-resistant prostate cancer (mCRPC), and further explore the differences in rPFS and PPS between patients exhibiting single- or multicategory progression patterns.

DESIGN, SETTING, AND PARTICIPANTS

This post hoc, retrospective secondary analysis was based on individual patient data from LATITUDE (phase 3 randomized mHSPC study) and COU-AA-302 (phase 3 randomized mCRPC study). Patients with complete imaging follow-up data and radiological progression were included in the analysis.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The rPFS and PPS in LATITUDE and COU-AA-302 were evaluated. The proportion of patients exhibiting each progression pattern was calculated, and a survival analysis was conducted using the Kaplan-Meier method.

RESULTS AND LIMITATIONS

Of the 489 mHSPC patients studied, 366 experienced single-category progression, while the remaining 123 patients (25.2%) exhibited simultaneous occurrence of different progressive events (multicategory radiological progression). Of the 534 mCRPC patients studied, 390 experienced single-category progression, while the remaining 144 patients (27.0%) experienced multicategory progressive events. Among mCRPC patients, the rPFS of bone progression was the shortest. In contrast, among mHSPC patients, the rPFS of target lesion enlargement is the shortest, followed by bone progression. Notably, patients experiencing a single-category progression pattern displayed comparable rPFS to but significantly longer PPS than those experiencing multicategory progression patterns (PPS mHSPC cohort: 21.5 vs 6.9 mo, p < 0.0001; mCRPC cohort: 23.6 vs 15.7 mo, p < 0.0001). The study is limited by its hypothesis-generating nature. Therefore, the observed phenomena in our research necessitate validation through future prospective studies.

CONCLUSIONS

Patients who experience multicategory radiological progression represent a significant proportion, accounting for approximately 25% of all men with mHSPC or mCRPC. Patients with multicategory radiological progression patterns had similar rPFS to but significantly shorter PPS than those experiencing single-category progression patterns. In future clinical trials and clinical practice, radiological progression patterns should be recognized as a crucial determinant of prognosis, while also serving as the stratification or inclusion criteria for second-line treatment clinical trials.

PATIENT SUMMARY

In this study, we observed that among men with metastatic prostate cancer, those who experienced two or more radiological events during a single visit had a worse prognosis than those who experienced isolated radiological events.

Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1

OBJECTIVES

To compare liver metastases changes in CT assessed by radiologists using RECIST 1.1 and with aided simultaneous deep learning-based volumetric lesion changes analysis.

METHODS

A total of 86 abdominal CT studies from 43 patients (prior and current scans) of abdominal CT scans of patients with 1041 liver metastases (mean = 12.1, std = 11.9, range 1-49) were analyzed. Two radiologists performed readings of all pairs; conventional with RECIST 1.1 and with computer-aided assessment. For computer-aided reading, we used a novel simultaneous multi-channel 3D R2U-Net classifier trained and validated on other scans. The reference was established by having an expert radiologist validate the computed lesion detection and segmentation. The results were then verified and modified as needed by another independent radiologist. The primary outcome measure was the disease status assessment with the conventional and the computer-aided readings with respect to the reference.

RESULTS

For conventional and computer-aided reading, there was a difference in disease status classification in 40 out of 86 (46.51%) and 10 out of 86 (27.9%) CT studies with respect to the reference, respectively. Computer-aided reading improved conventional reading in 30 CT studies by 34.5% for two readers (23.2% and 46.51%) with respect to the reference standard. The main reason for the difference between the two readings was lesion volume differences (p = 0.01).

CONCLUSIONS

AI-based computer-aided analysis of liver metastases may improve the accuracy of the evaluation of neoplastic liver disease status.

CLINICAL RELEVANCE STATEMENT

AI may aid radiologists to improve the accuracy of evaluating changes over time in metastasis of the liver.

KEY POINTS

• Classification of liver metastasis changes improved significantly in one-third of the cases with an automatically generated comprehensive lesion and lesion changes report. • Simultaneous deep learning changes detection and volumetric assessment may improve the evaluation of liver metastases temporal changes potentially improving disease management.

An MRI-based machine learning radiomics can predict short-term response to neoadjuvant chemotherapy in patients with cervical squamous cell carcinoma: A multicenter study

BACKGROUND AND PURPOSE

Neoadjuvant chemotherapy (NACT) has become an essential component of the comprehensive treatment of cervical squamous cell carcinoma (CSCC). However, not all patients respond to chemotherapy due to individual differences in sensitivity and tolerance to chemotherapy drugs. Therefore, accurately predicting the sensitivity of CSCC patients to NACT was vital for individual chemotherapy. This study aims to construct a machine learning radiomics model based on magnetic resonance imaging (MRI) to assess its efficacy in predicting NACT susceptibility among CSCC patients.

METHODS

This study included 234 patients with CSCC from two hospitals, who were divided into a training set (n = 180), a testing set (n = 20), and an external validation set (n = 34). Manual radiomic features were extracted from transverse section MRI images, and feature selection was performed using the recursive feature elimination (RFE) method. A prediction model was then generated using three machine learning algorithms, namely logistic regression, random forest, and support vector machines (SVM), for predicting NACT susceptibility. The model's performance was assessed based on the area under the receiver operating characteristic curve (AUC), accuracy, and sensitivity.

RESULTS

The SVM approach achieves the highest scores on both the testing set and the external validation set. In the testing set and external validation set, the AUC of the model was 0.88 and 0.764, and the accuracy was 0.90 and 0.853, the sensitivity was 0.93 and 0.962, respectively.

CONCLUSIONS

Machine learning radiomics models based on MRI images have achieved satisfactory performance in predicting the sensitivity of NACT in CSCC patients with high accuracy and robustness, which has great significance for the treatment and personalized medicine of CSCC patients.

High-intensity focused ultrasound versus transarterial chemoembolization for hepatocellular carcinoma: a meta-analysis

PURPOSE

The application of high-intensity focused ultrasound (HIFU) in hepatocellular carcinoma (HCC) was promising. However, whether the effect of HIFU is comparable with that of transarterial chemoembolization (TACE) has not been determined.

MATERIALS AND METHODS

PubMed, Embase, Cochrane Library, Web of Science, WanFang Data, CqVip, CNKI, and CBM databases were searched for randomized controlled trials (RCTs), cohort studies, and case-control studies. The methodological quality of each study was evaluated. When there is no statistical heterogeneity, the fixed effect model would be used to merge data. Otherwise, the random effect model would be utilized. Sensitivity analyses were conducted by excluding one study each time. Subgroup analyses were conducted based on age, sex, tumor number, relative number of the patients with Child-Pugh C grade in each group, the percentage of patients with Child-Pugh C grade in the whole study, and tumor load. Publication bias was evaluated by Egger's test and Begg's test.

RESULTS

Six cohort studies including 188 patients from HIFU group and 224 patients from TACE group were obtained for further analysis. The meta-analysis suggested HIFU and TACE showed no differences in postoperative 1-year overall survival (OS) rate, tumor response (including complete response, partial response, stable disease, and progressive disease), and postoperative complications. Moreover, compared with TACE, HIFU showed higher postoperative 6-month and 2-year OS rates. Subgroup analyses, meta regression analysis and sensitivity analyses indicated the findings above were reliable. Additionally, no potential publication bias was detected.

CONCLUSION

For HCC, when compared with TACE, HIFU might show comparable safety but better effect. Considering the limitations of current studies, more well-designed studies are needed to validate our conclusion.

DIAGNOSTICS OF LYMPHOGENIC METASTASIS IN PATIENTS WITH RECTAL CANCER BY COMBINING MRI WITH BLOOD CEA ASSESSMENT

AIM

To improve the diagnostics of lymphogenic metastasis in patients with rectal cancer (RCa) by combining magnetic resonance imaging (MRI) with the blood carcinoembryonic antigen (CEA) level assessment.

MATERIALS AND METHODS

We have systematized and analyzed the results of the examination and treatment of 77 patients with stage II-III rectal adenocarcinoma (T2-3N0-2M0). Before the start of neoadjuvant treatment as well as 8 weeks after its completion, computed tomography (CT) and MRI were performed. We analyzed such prognostic criteria as the size, shape, and structure of lymph nodes as well as the patterns of contrast accumulation. As a prognostic marker, CEA levels in the blood of patients with RCa before surgical treatment were assessed.

RESULTS

Radiological exams showed a rounded shape and heterogeneous structure to be the most informative for predicting metastatic lymph node damage, increasing the probability by 4.39 and 4.98 times, respectively. After neoadjuvant treatment, the percentage of positive histopathological reports on lymph node involvement decreased significantly to 21.6% (р ˂ 0.001). MRI showed 76% sensitivity and 48% specificity for assessing lymphogenic metastasis. CEA levels differed significantly between stages II and III (N1-2) (р ˂ 0.032) with a threshold value of 3.95 ng/ml.

CONCLUSIONS

In order to increase the effectiveness of the diagnosis of lymphogenic metastasis using radiological examination methods in RCa patients, such prognostic criteria as the round shape and heterogeneous structure of the lymph nodes and the threshold level of CEA should be considered.

Pervasiveness of HLA allele-specific expression loss across tumor types

BACKGROUND

Efficient presentation of mutant peptide fragments by the human leukocyte antigen class I (HLA-I) genes is necessary for immune-mediated killing of cancer cells. According to recent reports, patient HLA-I genotypes can impact the efficacy of cancer immunotherapy, and the somatic loss of HLA-I heterozygosity has been established as a factor in immune evasion. While global deregulated expression of HLA-I has also been reported in different tumor types, the role of HLA-I allele-specific expression loss - that is, the preferential RNA expression loss of specific HLA-I alleles - has not been fully characterized in cancer.

METHODS

Here, we use RNA and whole-exome sequencing data to quantify HLA-I allele-specific expression (ASE) in cancer using our novel method arcasHLA-quant.

RESULTS

We show that HLA-I ASE loss in at least one of the three HLA-I genes is a pervasive phenomenon across TCGA tumor types. In pancreatic adenocarcinoma, tumor-specific HLA-I ASE loss is associated with decreased overall survival specifically in the basal-like subtype, a finding that we validated in an independent cohort through laser-capture microdissection. Additionally, we show that HLA-I ASE loss is associated with poor immunotherapy outcomes in metastatic melanoma through retrospective analyses.

CONCLUSIONS

Together, our results highlight the prevalence of HLA-I ASE loss and provide initial evidence of its clinical significance in cancer prognosis and immunotherapy treatment.

Assessing the Increased Variability in Individual Lesion Kinetics During Immunotherapy: Does It Exist, and Does It Matter?

PURPOSE

Several studies have raised the hypothesis that immunotherapy may exacerbate the variability in individual lesions, increasing the risk of observing divergent kinetic profiles within the same patient. This questions the use of the sum of the longest diameter to follow the response to immunotherapy. Here, we aimed to study this hypothesis by developing a model that estimates the different sources of variability in lesion kinetics, and we used this model to evaluate the impact of this variability on survival.

METHODS

We relied on a semimechanistic model to follow the nonlinear kinetics of lesions and their impact on the risk of death, adjusted on organ location. The model incorporated two levels of random effects to characterize both between- and within-patient variability in response to treatment. The model was estimated on 900 patients from a phase III randomized trial evaluating programmed death-ligand 1 checkpoint inhibitor atezolizumab versus chemotherapy in patients with second-line metastatic urothelial carcinoma (IMvigor211).

RESULTS

The within-patient variability in the four parameters that characterize individual lesion kinetics represented between 12% and 78% of the total variability during chemotherapy. Similar results were obtained during atezolizumab, except for the durability of the treatment effects, for which the within-patient variability was markedly larger than during chemotherapy (40% v 12%, respectively). Accordingly, the occurrence of divergent profile consistently increased over time in patients treated with atezolizumab and was equal to about 20% after 1 year of treatment. Finally, we show that accounting for the within-patient variability provided a better prediction of most at-risk patients than a model relying solely on the sum of the longest diameter.

CONCLUSION

Within-patient variability provides valuable information for the assessment of treatment efficacy and the detection of at-risk patients.

An open label phase II study of safety and clinical activity of naltrexone for treatment of hormone refractory metastatic breast cancer

The opioid receptor (OR) antagonist naltrexone inhibits estrogen receptor-α (ER) function in model systems. The goal of this study was to determine the clinical activity of naltrexone in patients with ER-positive metastatic breast cancer. Patients with hormone receptor positive metastatic breast cancer were enrolled on a phase II study of naltrexone. An escalating dose scheme was used to reach the planned dose of 50 mg daily. The primary objective of the study was to evaluate response to therapy as measured by stabilization or reduction of the tumor Maximum Standardized Uptake Value (SUVmax) at 4 weeks by PET-CT scan. The secondary objectives included safety assessment and tumor SUVmax at 8 weeks. Out of 13 patients we enrolled, 8 patients had serial PET-CT scans that were evaluable for response. Of these 8 patients, 5 had stable or decreased SUVmax values at 4 weeks and 3 had clinical or imaging progression. Median time to progression was short at 7 weeks. Naltrexone was well tolerated. There were no discontinuations due to toxicity and no grade 3 or 4 toxicities were noted. Naltrexone showed modest activity in this short study suggesting the contribution of opioid receptors in ER-positive breast cancer. Our data do not support further development of naltrexone in hormone refractory breast cancer. It is possible that more potent peripherally acting OR antagonists may have a greater effect. (ClinicalTrials.gov Identifier: NCT00379197 September 21, 2006).

Is CT or FDG-PET more useful for evaluation of the treatment response in metastatic HER2-positive breast cancer? a case report and literature review

Response evaluation criteria in solid tumors version 1.1 (RECIST ver1.1) has been widely adopted to evaluate treatment efficacy in solid tumors, including breast cancer (BC), in clinical trials and clinical practice. RECIST is based mainly on computed tomography (CT) images, and the role of fluorodeoxyglucose-positron emission tomography (FDG-PET) is limited. However, because the rate of tumor shrinkage on CT does not necessarily reflect the potential remaining tumor cells, there may be a discrepancy between the treatment response and prognosis in some cases. Here we report a case of metastatic human epidermal growth factor receptor 2 (HER2)-positive BC where FDG-PET was preferable to CT for evaluation of the treatment response. A 40-year-old woman became aware of a lump in her right breast in September 201X. She was pregnant and underwent further examinations, including a biopsy, in November. The diagnosis was HER2-positive BC (cT2N2bM1, stage IV). Trastuzumab plus pertuzumab plus docetaxel (TPD) therapy was initiated in December 201X. CT performed in February 201X+1 showed cystic changes in the metastatic lesions in the liver, and the treatment response was stable disease (SD) according to RECIST. However, FDG-PET in March 201X+1 did not detect abnormal uptake of FDG in the hepatic lesions. The disease remained stable thereafter. Thus, tumor shrinkage may not be apparent in situations where the response to treatment results in rapid changes in blood flow within the tumor, which is associated with cystic changes. When patients with hypervascular liver metastases receive treatment with highly effective regimens, the target lesion may show cystic changes rather than shrinkage, as observed in the present case. Therefore, FDG-PET is sometimes superior to CT in judging a tumor response.

Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-Net

The identification and quantification of liver lesions changes in longitudinal contrast enhanced CT (CECT) scans is required to evaluate disease status and to determine treatment efficacy in support of clinical decision-making. This paper describes a fully automatic end-to-end pipeline for liver lesion changes analysis in consecutive (prior and current) abdominal CECT scans of oncology patients. The three key novelties are: (1) SimU-Net, a simultaneous multi-channel 3D R2U-Net model trained on pairs of registered scans of each patient that identifies the liver lesions and their changes based on the lesion and healthy tissue appearance differences; (2) a model-based bipartite graph lesions matching method for the analysis of lesion changes at the lesion level; (3) a method for longitudinal analysis of one or more of consecutive scans of a patient based on SimU-Net that handles major liver deformations and incorporates lesion segmentations from previous analysis. To validate our methods, five experimental studies were conducted on a unique dataset of 3491 liver lesions in 735 pairs from 218 clinical abdominal CECT scans of 71 patients with metastatic disease manually delineated by an expert radiologist. The pipeline with the SimU-Net model, trained and validated on 385 pairs and tested on 249 pairs, yields a mean lesion detection recall of 0.86±0.14, a precision of 0.74±0.23 and a lesion segmentation Dice of 0.82±0.14 for lesions > 5 mm. This outperforms a reference standalone 3D R2-UNet mdel that analyzes each scan individually by ∼50% in precision with similar recall and Dice score on the same training and test datasets. For lesions matching, the precision is 0.86±0.18 and the recall is 0.90±0.15. For lesion classification, the specificity is 0.97±0.07, the precision is 0.85±0.31, and the recall is 0.86±0.23. Our new methods provide accurate and comprehensive results that may help reduce radiologists' time and effort and improve radiological oncology evaluation.

Automatic segmentation of hepatic metastases on DWI images based on a deep learning method: assessment of tumor treatment response according to the RECIST 1.1 criteria

BACKGROUND

Evaluation of treated tumors according to Response Evaluation Criteria in Solid Tumors (RECIST) criteria is an important but time-consuming task in medical imaging. Deep learning methods are expected to automate the evaluation process and improve the efficiency of imaging interpretation.

OBJECTIVE

To develop an automated algorithm for segmentation of liver metastases based on a deep learning method and assess its efficacy for treatment response assessment according to the RECIST 1.1 criteria.

METHODS

One hundred and sixteen treated patients with clinically confirmed liver metastases were enrolled. All patients had baseline and post-treatment MR images. They were divided into an initial (n = 86) and validation cohort (n = 30) according to the examined time. The metastatic foci on DWI images were annotated by two researchers in consensus. Then the treatment responses were assessed by the two researchers according to RECIST 1.1 criteria. A 3D U-Net algorithm was trained for automated liver metastases segmentation using the initial cohort. Based on the segmentation of liver metastases, the treatment response was assessed automatically with a rule-based program according to the RECIST 1.1 criteria. The segmentation performance was evaluated using the Dice similarity coefficient (DSC), volumetric similarity (VS), and Hausdorff distance (HD). The area under the curve (AUC) and Kappa statistics were used to assess the accuracy and consistency of the treatment response assessment by the deep learning model and compared with two radiologists [attending radiologist (R1) and fellow radiologist (R2)] in the validation cohort.

RESULTS

In the validation cohort, the mean DSC, VS, and HD were 0.85 ± 0.08, 0.89 ± 0.09, and 25.53 ± 12.11 mm for the liver metastases segmentation. The accuracies of R1, R2 and automated segmentation-based assessment were 0.77, 0.65, and 0.74, respectively, and the AUC values were 0.81, 0.73, and 0.83, respectively. The consistency of treatment response assessment based on automated segmentation and manual annotation was moderate [K value: 0.60 (0.34-0.84)].

CONCLUSION

The deep learning-based liver metastases segmentation was capable of evaluating treatment response according to RECIST 1.1 criteria, with comparable results to the junior radiologist and superior to that of the fellow radiologist.

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.

Circulating cell-free messenger RNA enables non-invasive pan-tumour monitoring of melanoma therapy independent of the mutational genotype

BACKGROUND

Plasma-derived tumour-specific cell-free nucleic acids are increasingly utilized as a minimally invasive, real-time biomarker approach in many solid tumours. Circulating tumour DNA of melanoma-specific mutations is currently the best studied liquid biopsy biomarker for melanoma. However, the combination of hotspot genetic alterations covers only around 80% of all melanoma patients. Therefore, alternative approaches are needed to enable the follow-up of all genotypes, including wild-type.

METHODS

We identified KPNA2, DTL, BACE2 and DTYMK messenger RNA (mRNA) upregulated in melanoma versus nevi tissues by unsupervised data mining (N = 175 melanoma, N = 20 normal skin, N = 6 benign nevi) and experimentally confirmed differential mRNA expression in vitro (N = 18 melanoma, N = 8 benign nevi). Circulating cell-free RNA (cfRNA) was analysed in 361 plasma samples (collected before and during therapy) from 100 melanoma patients and 18 healthy donors. Absolute cfRNA copies were quantified on droplet digital PCR.

RESULTS

KPNA2, DTL, BACE2 and DTYMK cfRNA demonstrated high diagnostic accuracy between melanoma patients' and healthy donors' plasma (AUC > 86%, p < .0001). cfRNA copies increased proportionally with increasing tumour burden independently of demographic variables and even remained elevated in individuals with radiological absence of disease. Re-analysis of single-cell transcriptomes revealed a pan-tumour origin of cfRNA, including endothelial, cancer-associated fibroblasts, macrophages and B cells beyond melanoma cells as cellular sources. Low baseline cfRNA levels were associated with significantly longer progression-free survival (PFS) (KPNA2 HR = .54, p = .0362; DTL HR = .60, p = .0349) and overall survival (KPNA2 HR = .52, p = .0237; BACE2 HR = .55, p = .0419; DTYMK HR = .43, p = .0393). Lastly, we found that cfRNA copies significantly increased during therapy in non-responders compared to responders regardless of therapy and mutational subtypes and that the increase of KPNA2 (HR = 1.73, p = .0441) and DTYMK (HR = 1.82, p = .018) cfRNA during therapy was predictive of shorter PFS.

CONCLUSIONS

In sum, we identified a new panel of cfRNAs for a pan-tumour liquid biopsy approach and demonstrated its utility as a prognostic, therapy-monitoring tool independent of the melanoma mutational genotype.

Radiomic and Volumetric Measurements as Clinical Trial Endpoints—A Comprehensive Review

Simple Summary

The extraction of quantitative data from standard-of-care imaging modalities offers opportunities to improve the relevance and salience of imaging biomarkers used in drug development. This review aims to identify the challenges and opportunities for discovering new imaging-based biomarkers based on radiomic and volumetric assessment in the single-site solid tumor sites: breast cancer, rectal cancer, lung cancer and glioblastoma. Developing approaches to harmonize three essential areas: segmentation, validation and data sharing may expedite regulatory approval and adoption of novel cancer imaging biomarkers.

Abstract

Clinical trials for oncology drug development have long relied on surrogate outcome biomarkers that assess changes in tumor burden to accelerate drug registration (i.e., Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1) criteria). Drug-induced reduction in tumor size represents an imperfect surrogate marker for drug activity and yet a radiologically determined objective response rate is a widely used endpoint for Phase 2 trials. With the addition of therapies targeting complex biological systems such as immune system and DNA damage repair pathways, incorporation of integrative response and outcome biomarkers may add more predictive value. We performed a review of the relevant literature in four representative tumor types (breast cancer, rectal cancer, lung cancer and glioblastoma) to assess the preparedness of volumetric and radiomics metrics as clinical trial endpoints. We identified three key areas—segmentation, validation and data sharing strategies—where concerted efforts are required to enable progress of volumetric- and radiomics-based clinical trial endpoints for wider clinical implementation.

Study protocol: Randomized, open-label, non-inferiority clinical trial for evaluating the clinical and pathological response rates to neoadjuvant hormone therapy and chemotherapy in patients with luminal-subtype breast tumors

Background

Despite neoadjuvant hormone therapy (NHT) is being underused, it is an effective treatment for luminal tumors at a lower cost and with fewer side effects compared to those associated with neoadjuvant chemotherapy (NCT). The lack of robust comparative data between NHT and NCT is a factor that limits its use in clinical practice.

Methods

This study will be a randomized, open-label, non-inferiority clinical trial. Patients diagnosed with HER2-negative luminal-subtype breast cancer will be identified at the time of diagnosis. Menopausal patients randomized for NHT should receive anastrozole for at least six months. Premenopausal women should receive anastrozole associated with subcutaneous goserelin acetate every 12 weeks for at least six months. Patients randomized for NCT will receive a standard institutional regimen based on anthracyclines and taxanes. Sample size was calculated considering the CPS + EG as a method for evaluating response and prognosis, where a score <3 was defined as good. The non-inferiority margin for NHT was set at 15%. The study considered a power of 80%, a significance level of 5%, and an outcome proportion in each group of 69%, resulting in 118 patients in each group. We estimated at 10% of losses, resulting in a sample of 130 patients in each group.

Conclusion

The non-inferiority of NHT in relation to NCT will provide further evidence that replacing NCT with NHT is safe and effective in eligible patients, which is particularly relevant for populations with limited access to health services and for institutions with few available resources.

Clinical Characteristics, Prognostic Factors and Treatment Outcomes of Patients with Bone-Only Metastatic Breast Cancer

Introduction

Bone is the most frequent site of breast cancer metastasis. Differences between those who present with de novo bone-only metastasis (BOM) and those who progress to bone-only disease following a diagnosis of early-stage breast cancer are not clear. Such differences in clinical course might have an impact on the aggressiveness of treatment. This study presents the clinical and pathological features, along with treatment outcomes, of breast cancer patients with BOM in relation to the timing and type of bone metastasis.

Patients and Methods

Patients with breast cancer and BOM were retrospectively reviewed. De novo BOM was defined as bone metastasis diagnosed at presentation or within the first 4 months of follow-up. Treatment outcomes of patients with de novo, compared to those with subsequent BOM, are presented.

Results

242 patients, median age (range) at diagnosis was 52 (27–80) years were enrolled. The majority of the patients (77.3%) had de novo BOM with multiple sites of bone involvement (82.6%). At a median follow-up of 37.7 months, the median overall survival (OS) for patients with de novo BOM disease was significantly shorter than those who developed so subsequently; 40.8 months (95% CI, 51.1–184.1) compared to 80.9 months (95% CI, 36.4–47.9), p < 0.001. Tumor grade, hormone receptor status and type of bone lesions (lytic versus sclerotic) had a significant impact on survival outcomes.

Conclusion

Breast cancer with de novo BOM is a distinct clinical entity with unfavorable prognosis and is associated with shorter survival. Several risk factors for poor outcomes were identified and might inform treatment plans.

iRECIST and atypical patterns of response to immuno-oncology drugs

With the advent of immunotherapy as one of the keystones of the treatment of our patients with cancer, a number of atypical patterns of response to these agents has been identified. These include pseudoprogression, where the tumor initially shows objective growth before decreasing in size, and hyperprogression, hypothesized to be a drug-induced acceleration of the tumor burden. Despite it being >10 years since the first immune-oncology drug was approved, neither the biology behind these paradoxical responses has been well understood, nor their incidence, identification criteria, predictive biomarkers, or clinical impact have been fully described. Immune-based Response Evaluation Criteria in Solid Tumors (iRECIST) guidelines have been published as a revision to the RECIST V.1.1 criteria for use in trials of immunotherapeutics, and the iRECIST subcommittee (of the RECIST Working Group) is working on elucidating these aspects, with data sharing a current major challenge to move forward with this unmet need in immuno-oncology.

Materials-driven approaches to understand extrinsic drug resistance in cancer

Metastatic cancer has a poor prognosis, because it is broadly disseminated and associated with both intrinsic and acquired drug resistance. Critical unmet needs in effectively killing drug resistant cancer cells include overcoming the drug desensitization characteristics of some metastatic cancers/lesions, and tailoring therapeutic regimens to both the tumor microenvironment and the genetic profiles of the resident cancer cells. Bioengineers and materials scientists are developing technologies to determine how metastatic sites exclude therapies, and how extracellular factors (including cells, proteins, metabolites, extracellular matrix, and abiotic factors) at metastatic sites significantly affect drug pharmacodynamics. Two looming challenges are determining which feature, or combination of features, from the tumor microenvironment drive drug resistance, and what the relative impact is of extracellular signals vs. intrinsic cell genetics in determining drug response. Sophisticated systems biology tools that can de-convolve a crowded network of signals and responses, as well as controllable microenvironments capable of providing discrete and tunable extracellular cues can help us begin to interrogate the high dimensional interactions governing drug resistance in patients.

Safety, Feasibility, and Merits of Longitudinal Molecular Testing of Multiple Metastatic Sites to Inform mTNBC Patient Treatment in the Intensive Trial of Omics in Cancer

Patients with metastatic triple-negative breast cancer (mTNBC) have poor outcomes. The Intensive Trial of Omics in Cancer (ITOMIC) sought to determine the feasibility and potential efficacy of informing treatment decisions through multiple biopsies of mTNBC deposits longitudinally over time, accompanied by analysis using a distributed network of experts.

In the Intensive Trial of Omics in Cancer (ITOMIC), the feasibility and potential efficacy of informing treatment decisions through omics analysis of multiple biopsies of mTNBC deposits over time was assessed. An ITOMIC Tumor Board (ITB) that comprised experts discussed tumor profile findings and made treatment recommendations to each subject's physician. Study-directed omics analysis revealed that of the 31 enrolled subjects, two were found to have lung cancer, one a carcinoma of unknown primary site that and tumor samples from five subjects showed some receptor-positivity. Several subjects survived well beyond what would be expected for this patient group, supporting the merits of further investigation of this approach.

A Review on the Efficacy and Safety of Nab-Paclitaxel with Gemcitabine in Combination with Other Therapeutic Agents as New Treatment Strategies in Pancreatic Cancer

Pancreatic cancer has one of the highest mortality rates among cancers, and a combination of nab-paclitaxel with gemcitabine remains the cornerstone of first-line therapy. However, major advances are required to achieve improvements in patient outcomes. For this reason, several research groups have proposed supplementing treatment with other therapeutic agents. Ongoing studies are being conducted to find the optimal treatment in a first-line setting. In this work, we used a search strategy to compare studies on the efficacy and safety of nab-paclitaxel with gemcitabine in combination with other therapeutic agents based on the criteria of the Preferred Reporting Items for Systematic Reviews. We found seven studies in different clinical phases that met the inclusion criteria. The seven therapeutic agents were ibrutinib, necuparanib, tarextumab, apatorsen, cisplatin, enzalutamide, and momelotinib. Although these therapeutic agents have different mechanisms of action, and molecular biology studies are still needed, the present review was aimed to answer the following question: which formulations of the nab-paclitaxel/gemcitabine regimen in combination with other therapeutic agents are safest for patients with previously untreated metastatic pancreas ductal adenocarcinoma? The triple regimen is emerging as the first-line option for patients with pancreatic cancer, albeit with some limitations. Thus, further studies of this regimen are recommended.

A Case of ALK-Rearranged Combined Lung Adenocarcinoma and Neuroendocrine Carcinoma with Diffuse Bone Metastasis and Partial Response to Alectinib

We report a rare case of stage IV pulmonary combined large-cell neuroendocrine carcinoma (LCNEC) and adenocarcinoma (ACA), both demonstrating anaplastic lymphoma kinase (ALK) rearrangement by IHC and FISH. This 61-year-old lifelong nonsmoking Asian woman presented with a cough, and after diagnosis and surgical treatment, completed four cycles of adjuvant cisplatin and etoposide chemotherapy. She subsequently developed recurrence with bony metastases of exclusively ALK-positive LCNEC. Alectinib was started, and the patient experienced a partial response.

Twenty Years On: RECIST as a Biomarker of Response in Solid Tumours an EORTC Imaging Group - ESOI Joint Paper

Response evaluation criteria in solid tumours (RECIST) v1.1 are currently the reference standard for evaluating efficacy of therapies in patients with solid tumours who are included in clinical trials, and they are widely used and accepted by regulatory agencies. This expert statement discusses the principles underlying RECIST, as well as their reproducibility and limitations. While the RECIST framework may not be perfect, the scientific bases for the anticancer drugs that have been approved using a RECIST-based surrogate endpoint remain valid. Importantly, changes in measurement have to meet thresholds defined by RECIST for response classification within thus partly circumventing the problems of measurement variability. The RECIST framework also applies to clinical patients in individual settings even though the relationship between tumour size changes and outcome from cohort studies is not necessarily translatable to individual cases. As reproducibility of RECIST measurements is impacted by reader experience, choice of target lesions and detection/interpretation of new lesions, it can result in patients changing response categories when measurements are near threshold values or if new lesions are missed or incorrectly interpreted. There are several situations where RECIST will fail to evaluate treatment-induced changes correctly; knowledge and understanding of these is crucial for correct interpretation. Also, some patterns of response/progression cannot be correctly documented by RECIST, particularly in relation to organ-site (e.g. bone without associated soft-tissue lesion) and treatment type (e.g. focal therapies). These require specialist reader experience and communication with oncologists to determine the actual impact of the therapy and best evaluation strategy. In such situations, alternative imaging markers for tumour response may be used but the sources of variability of individual imaging techniques need to be known and accounted for. Communication between imaging experts and oncologists regarding the level of confidence in a biomarker is essential for the correct interpretation of a biomarker and its application to clinical decision-making. Though measurement automation is desirable and potentially reduces the variability of results, associated technical difficulties must be overcome, and human adjudications may be required.

Imaging response assessment for oncology: An algorithmic approach

Treatment response assessment by imaging plays a vital role in evaluating changes in solid tumors during oncology therapeutic clinical trials. Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 is the reference standard imaging response criteria and provides details regarding image acquisition, image interpretation and categorical response classification. While RECIST 1.1 is applied for the majority of clinical trials in solid tumors, other criteria and modifications have been introduced when RECIST 1.1 outcomes may be incomplete. Available criteria beyond RECIST 1.1 can be explored in an algorithmic fashion dependent on imaging modality, tumor type and method of treatment. Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) is available for use with PET/CT. Modifications to RECIST 1.1 can be tumor specific, including mRECIST for hepatocellular carcinoma and mesothelioma. Choi criteria for gastrointestinal stromal tumors incorporate tumor density with alterations to categorical response thresholds. Prostate Cancer Working Group 3 (PCWG3) imaging criteria combine RECIST 1.1 findings with those of bone scans. In addition, multiple response criteria have been created to address atypical imaging responses in immunotherapy.

The Role of Change Rates of CYFRA21-1 and CEA in Predicting Chemotherapy Efficacy for Non-Small-Cell Lung Cancer

BACKGROUND

Cytokeratin 19 fragment 21-1 (CYFRA21-1) and carcinoembryonic antigen (CEA) are effective prognostic biomarkers for lung cancer. This study investigated the predictive effects of change rates of CYFRA21-1 and CEA before and after the first cycles of chemotherapy on advanced IIIb/IIIc or IV stage non-small-cell lung cancer (NSCLC) patients.

METHODS

Data of 103 NSCLC patients who received chemotherapy in Zhejiang Provincial People's Hospital from February 2018 to November 2020 were retrospectively analyzed. All patients received platinum doublet chemotherapy for at least 2 cycles. CYFRA21-1 and CEA levels of patients were detected before and after the first chemotherapy cycle, respectively. After the second cycle, the efficacy was evaluated, and patients were divided into the disease control (DC) and progressive disease (PD) groups. The generalized linear model (GLM) and linear trend test assessed the relationship between change rates of CYFRA21-1 and CEA levels and chemotherapeutic efficacy before and after chemotherapy. Moreover, the receiver operating characteristic (ROC) curve determined the predictive value of change rates of CYFRA21-1 and CEA on chemotherapeutic efficacy.

RESULTS

After the second chemotherapeutic cycle, there were 92 patients in the DC group and 11 in the PD group. GLM and linear trend test both indicated that change rates of CYFRA21-1 and CEA were inversely correlated with chemotherapeutic efficacy for NSCLC. Change rates of CYFRA21-1 and CEA were used to predict area under the ROC curve of chemotherapeutic efficacy (0.87, 0.71-1.00), which is better than single index prediction of CYFRA21-1 (0.71, 0.49-0.94) or CEA change rate (0.85, 0.69-1.00) (p < 0.001).

CONCLUSION

Before and after chemotherapy of the first cycle for advanced NSCLC patients, combining serum CYFRA21-1 and CEA levels could increase sensitivity and specificity to predict the chemotherapeutic efficacy and guide the following therapy of advanced NSCLC patients.

Palbociclib in breast cancer neoadjuvant setting

Cyclin-dependent kinase 4/6 inhibitors represent a major advance in breast cancer treatment, emerging as the standard of care of the initial treatment of hormone receptor-positive and HER2-negative metastatic breast cancer. Their activity in this subset of patients leads to interest in their use in the adjuvant and neoadjuvant settings. This case report presents a real-life case of cyclin-dependent kinase 4/6 inhibitors use in a patient initially considered to have stage IV luminal HER2-negative breast cancer with liver metastasis. The discrepancy of treatment response between the breast tumor and liver node led to a repetition of the liver biopsy, which revealed metastasis of a neuroendocrine tumor of unknown primary. The breast tumor showed a partial response, and the initial therapeutic strategy was then redefined for curative intent. While cyclin-dependent kinase 4/6 inhibitors are not yet approved for clinical practice in the neo / adjuvant treatment of hormone receptor-positive breast cancer, this case report portrays a successful example of its application in a neoadjuvant setting.

Therapeutic Potential of Antibody-Drug Conjugate-Based Therapy in Head and Neck Cancer: A Systematic Review

BACKGROUND

Antibody-drug conjugates (ADCs) are designed to deliver potent cytotoxic agents into tumor tissues. During the last two decades, a plethora of ADCs have been successfully developed and used for several indications, including hematologic and solid tumors. In this work, we systematically reviewed the progress in ADC development for the treatment of HNC.

METHODS

This review was registered in PROSPERO database. A comprehensive search was conducted following PRISMA guidelines and using PubMed, Scopus and Web of Science database.

RESULTS

In total, 19 studies were included. Due to the significant heterogeneity of the outcome measures, meta-analysis was not performed, and data were summarized in tables. HNC results are poorly represented in the cohorts of completed clinical trials; published data are mostly focused on safety evaluation rather than efficacy of ADCs.

CONCLUSIONS

Although several novel agents against a wide range of different antigens were investigated, showing promising results at a preclinical level, most of the targets reported in this review are not specific for HNC; hence, the development of ADCs tailored for the HNC phenotype could open up new therapeutic perspectives. Moreover, the results from the present systematic review call attention to how limited is the application of current clinical trials in HNC.

Orai3-Mediates Cisplatin-Resistance in Non-Small Cell Lung Cancer Cells by Enriching Cancer Stem Cell Population through PI3K/AKT Pathway

Simple Summary

Lung cancer is recognized for having a very poor prognosis with an overall survival rate of 5-years not exceeding 15%. Platinum-doublet therapy is the most current chemotherapeutic treatment used to treat lung tumors. However, resistance to such drugs evolves rapidly in patients with non-small cell lung cancer (NSCLC) and is one of the major reasons behind therapy failure. Tumor recurrence due to chemoresistance is mainly attributed to the presence of cancer stem cells (CSCs) subpopulations. Thus, the identification of resistance actors and markers is necessary. The Orai3 channel has been recently identified as a predictive marker of metastasis and survival in resectable NSCLC tumors. Our results show, for the first time, that the Orai3 channel is able to induce chemoresistance by enriching CSCs population. Our findings present Orai3 as a promising predictive biomarker which could help with selecting chemotherapeutic drugs.

Abstract

The development of the resistance to platinum salts is a major obstacle in the treatment of non-small cell lung cancer (NSCLC). Among the reasons underlying this resistance is the enrichment of cancer stem cells (CSCs) populations. Several studies have reported the involvement of calcium channels in chemoresistance. The Orai3 channel is overexpressed and constitutes a predictive marker of metastasis in NSCLC tumors. Here, we investigated its role in CSCs populations induced by Cisplatin (CDDP) in two NSCLC cell lines. We found that CDDP treatment increased Orai3 expression, but not Orai1 or STIM1 expression, as well as an enhancement of CSCs markers. Moreover, Orai3 silencing or the reduction of extracellular calcium concentration sensitized the cells to CDDP and led to a reduction in the expression of Nanog and SOX-2. Orai3 contributed to SOCE (Store-operated Calcium entry) in both CDDP-treated and CD133⁺ subpopulation cells that overexpress Nanog and SOX-2. Interestingly, the ectopic overexpression of Orai3, in the two NSCLC cell lines, lead to an increase of SOCE and expression of CSCs markers. Furthermore, CD133⁺ cells were unable to overexpress neither Nanog nor SOX-2 when incubated with PI3K inhibitor. Finally, Orai3 silencing reduced Akt phosphorylation. Our work reveals a link between Orai3, CSCs and resistance to CDDP in NSCLC cells.

Response criteria for intraocular retinoblastoma: RB-RECIST

Standardized guidelines for assessing tumor response to therapy are essential for designing and conducting clinical trials. The Response Evaluation Criteria In Solid Tumors (RECIST) provide radiological standards for assessment of solid tumors. However, no such guidelines exist for the evaluation of intraocular cancer, and ocular oncology clinical trials have largely relied on indirect measures of therapeutic response-such as progression-free survival-to evaluate the efficacy of treatment agents. Herein, we propose specific criteria for evaluating treatment response of retinoblastoma, the most common pediatric intraocular cancer, and emphasize a multimodal imaging approach for comprehensive assessment of retinoblastoma tumors in clinical trials.

Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives

OBJECTIVES

Radiomics is the extraction of quantitative data from medical imaging, which has the potential to characterise tumour phenotype. The radiomics approach has the capacity to construct predictive models for treatment response, essential for the pursuit of personalised medicine. In this literature review, we summarise the current status and evaluate the scientific and reporting quality of radiomics research in the prediction of treatment response in non-small-cell lung cancer (NSCLC).

METHODS

A comprehensive literature search was conducted using the PubMed database. A total of 178 articles were screened for eligibility and 14 peer-reviewed articles were included. The radiomics quality score (RQS), a radiomics-specific quality metric emulating the TRIPOD guidelines, was used to assess scientific and reporting quality.

RESULTS

Included studies reported several predictive markers including first-, second- and high-order features, such as kurtosis, grey-level uniformity and wavelet HLL mean respectively, as well as PET-based metabolic parameters. Quality assessment demonstrated a low median score of + 2.5 (range - 5 to + 9), mainly reflecting a lack of reproducibility and clinical evaluation. There was extensive heterogeneity between studies due to differences in patient population, cancer stage, treatment modality, follow-up timescales and radiomics workflow methodology.

CONCLUSIONS

Radiomics research has not yet been translated into clinical use. Efforts towards standardisation and collaboration are needed to identify reproducible radiomic predictors of response. Promising radiomic models must be externally validated and their impact evaluated within the clinical pathway before they can be implemented as a clinical decision-making tool to facilitate personalised treatment for patients with NSCLC.

KEY POINTS

• The included studies reported several promising radiomic markers of treatment response in lung cancer; however, there was a lack of reproducibility between studies. • Quality assessment using the radiomics quality score (RQS) demonstrated a low median total score of + 2.5 (range - 5 to + 9). • Future radiomics research should focus on implementation of standardised radiomics features and software, together with external validation in a prospective setting.

Identifying response in colorectal liver metastases treated with bevacizumab: development of RECIST by combining contrast-enhanced and diffusion-weighted MRI

OBJECTIVES

Response evaluation criteria in solid tumors (RECIST) often fail to identify clinically meaningful response to bevacizumab-containing therapy in colorectal liver metastasis (CRLM). This study aimed to develop RECIST by combining contrast-enhanced and diffusion-weighted magnetic resonance imaging (MRI).

METHODS

A total of 126 patients with CRLM who underwent hepatic resection after bevacizumab-containing chemotherapy were split into initial analyses cohort (N = 42, with 76 indexed liver metastases) and validation cohort (N = 84). In lesion-based analyses, percentage decrease of arterial enhancement area and percentage increase of apparent diffusion coefficient (ADC) value from baseline to post-chemotherapy were measured. Their optimal cutoff values for distinguishing pathology-confirmed major and minor response were determined. Then, the developed RECIST (D-RECIST) was established by combining functional and size-based items. Survival relevance of D-RECIST and RECIST was examined in the validation cohort.

RESULTS

Percentage decrease of arterial enhancement area and increase of ADC value significantly differed between lesions of pathologic major or minor response, with optimal cutoffs of approximately 33% and 19%, respectively. Patients defined as responders by D-RECIST had a significantly longer median disease-free survival (DFS) than non-responders (p = 0.021; 12.9 versus 8.6 months). No significant difference was observed with RECIST (p = 0.524). In a Cox regression model, D-RECIST- but not RECIST-defined responses independently predicted the DFS (p = 0.034 and 0.811).

CONCLUSIONS

D-RECIST-defined responses provided significant prognostic information, and thus may serve as a better response evaluation approach than RECIST in CRLM treated with bevacizumab-containing therapy.

KEY POINTS

• Changes in arterial enhancement area and apparent diffusion coefficient value are associated with pathological response in colorectal liver metastases treated with bevacizumab. • The MRI-based response criteria developed by combining size-based and functional features can provide significant prognostic information.

Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients

BACKGROUND

Despite recent advance in immune therapy, great heterogeneity exists in the outcomes of colorectal cancer (CRC) patients. In this study, we aimed to analyze the immune-related gene (IRG) expression profiles from three independent public databases and develop an effective signature to forecast patient's prognosis.

METHODS

IRGs were collected from the ImmPort database. The CRC dataset from The Cancer Genome Atlas (TCGA) database was used to identify a prognostic gene signature, which was verified in another two CRC datasets from the Gene Expression Omnibus (GEO). Gene function enrichment analysis was conducted. A prognostic nomogram was built incorporating the IRG signature with clinical risk factors.

RESULTS

The three datasets had 487, 579, and 224 patients, respectively. A prognostic six-gene-signature (CCL22, LIMK1, MAPKAPK3, FLOT1, GPRC5B, and IL20RB) was developed through feature selection that showed good differentiation between the low- and high-risk groups in the training set (p < 0.001), which was later confirmed in the two validation groups (log-rank p < 0.05). The signature outperformed tumor TNM staging for survival prediction. GO and KEGG functional annotation analysis suggested that the signature was significantly enriched in metabolic processes and regulation of immunity (p < 0.05). When combined with clinical risk factors, the model showed robust prediction capability.

CONCLUSION

The immune-related six-gene signature is a reliable prognostic indicator for CRC patients and could provide insight for personalized cancer management.

Comparison of Various Phase I Combination Therapy Designs in Oncology for Evaluation of Early Tumor Shrinkage Using Simulations

There is still a lack of efficient designs for identifying the dose response in oncology combination therapies in early clinical trials. The concentration response relationship can be identified using the early tumor shrinkage time course, which has been shown to be a good early response marker of clinical efficacy. The performance of various designs using an exposure–tumor growth inhibition model was explored using simulations. Different combination effects of new drug M and cetuximab (reference therapy) were explored first assuming no effect of M on cetuximab (to investigate the type I error (α)), and subsequently assuming additivity or synergy between cetuximab and M. One‐arm, two‐arm, and four‐arm designs were evaluated. In the one‐arm design, 60 patients received cetuximab + M. In the two‐arm design, 30 patients received cetuximab and 30 received cetuximab + M. In the four‐arm design, in addition to cetuximab and cetuximab + M as standard doses, combination arms with lower doses of cetuximab were evaluated (15 patients/arm). Model‐based predictions or “simulated observations” of early tumor shrinkage at week 8 (ETS8) were compared between the different arms. With the same number of individuals, the one‐arm design showed better statistical power than other designs but led to strong inflation of α in case of misestimated reference for ETS8 value. The two‐arm design protected against this misestimation and, with the same total number of subjects, would provide higher statistical power than a four‐arm design. However, a four‐arm design would be helpful for exploring more doses of cetuximab in combination with M to better understand the interaction.

Enhanced Detection of Treatment Effects on Metastatic Colorectal Cancer with Volumetric CT Measurements for Tumor Burden Growth Rate Evaluation

PURPOSE

Mathematical models combined with new imaging technologies could improve clinical oncology studies. To improve detection of therapeutic effect in patients with cancer, we assessed volumetric measurement of target lesions to estimate the rates of exponential tumor growth and regression as treatment is administered.

EXPERIMENTAL DESIGN

Two completed phase III trials were studied (988 patients) of aflibercept or panitumumab added to standard chemotherapy for advanced colorectal cancer. Retrospectively, radiologists performed semiautomated measurements of all metastatic lesions on CT images. Using exponential growth modeling, tumor regression (d) and growth (g) rates were estimated for each patient's unidimensional and volumetric measurements.

RESULTS

Exponential growth modeling of volumetric measurements detected different empiric mechanisms of effect for each drug: panitumumab marginally augmented the decay rate [tumor half-life; d [IQR]: 36.5 days (56.3, 29.0)] of chemotherapy [d: 44.5 days (67.2, 32.1), two-sided Wilcoxon P = 0.016], whereas aflibercept more significantly slowed the growth rate [doubling time; g = 300.8 days (154.0, 572.3)] compared with chemotherapy alone [g = 155.9 days (82.2, 347.0), P ≤ 0.0001]. An association of g with overall survival (OS) was observed. Simulating clinical trials using volumetric or unidimensional tumor measurements, fewer patients were required to detect a treatment effect using a volumetric measurement-based strategy (32-60 patients) than for unidimensional measurement-based strategies (124-184 patients).

CONCLUSIONS

Combined tumor volume measurement and estimation of tumor regression and growth rate has potential to enhance assessment of treatment effects in clinical studies of colorectal cancer that would not be achieved with conventional, RECIST-based unidimensional measurements.

Comparing Circulating Tumor Cell Counts with Dynamic Tumor Size Changes as Predictor of Overall Survival: A Quantitative Modeling Framework

PURPOSE

Quantitative relationships between treatment-induced changes in tumor size and circulating tumor cell (CTC) counts, and their links to overall survival (OS), are lacking. We present a population modeling framework identifying and quantifying such relationships, based on longitudinal data collected in patients with metastatic colorectal cancer (mCRC) to evaluate the value of tumor size and CTC counts as predictors of OS.

EXPERIMENTAL DESIGN

A pharmacometric approach (i.e., population pharmacodynamic modeling) was used to characterize the changes in tumor size and CTC count and evaluate them as predictors of OS in 451 patients with mCRC treated with chemotherapy and targeted therapy in a prospectively randomized phase III study (CAIRO2).

RESULTS

A tumor size model of tumor quiescence and drug resistance was used to characterize the tumor size time-course, and was, in addition to the total normalized dose (i.e., of all administered drugs) in a given cycle, related to the CTC counts through a negative binomial model (CTC model). Tumor size changes did not contribute additional predictive value when the mean CTC count was a predictor of OS. Treatment reduced the typical mean count from 1.43 to 0.477 (HR = 3.94). The modeling framework was applied to explore whether dose modifications (increased and reduced) would result in a CTC count below 1/7.5 mL after 1 to 2 weeks of treatment.

CONCLUSIONS

Time-varying CTC counts can be useful for early predicting OS in patients with mCRC, and may therefore have potential for model-based treatment individualization. Although tumor size was connected to CTC, its link to OS was weaker.

Objective response rate assessment in oncology: Current situation and future expectations

The tumor objective response rate (ORR) is an important parameter to demonstrate the efficacy of a treatment in oncology. The ORR is valuable for clinical decision making in routine practice and a significant end-point for reporting the results of clinical trials. World Health Organization and Response Evaluation Criteria in Solid Tumors (RECIST) are anatomic response criteria developed mainly for cytotoxic chemotherapy. These criteria are based on the visual assessment of tumor size in morphological images provided by computed tomography (CT) or magnetic resonance imaging. Anatomic response criteria may not be optimal for biologic agents, some disease sites, and some regional therapies. Consequently, modifications of RECIST, Choi criteria and Morphologic response criteria were developed based on the concept of the evaluation of viable tumors. Despite its limitations, RECIST v1.1 is validated in prospective studies, is widely accepted by regulatory agencies and has recently shown good performance for targeted cancer agents. Finally, some alternatives of RECIST were developed as immune-specific response criteria for checkpoint inhibitors. Immune RECIST criteria are based essentially on defining true progressive disease after a confirmatory imaging. Some graphical methods may be useful to show longitudinal change in the tumor burden over time. Tumor tissue is a tridimensional heterogenous mass, and tumor shrinkage is not always symmetrical; thus, metabolic response assessments using positron emission tomography (PET) or PET/CT may reflect the viability of cancer cells or functional changes evolving after anticancer treatments. The metabolic response can show the benefit of a treatment earlier than anatomic shrinkage, possibly preventing delays in drug approval. Computer-assisted automated volumetric assessments, quantitative multimodality imaging in radiology, new tracers in nuclear medicine and finally artificial intelligence have great potential in future evaluations.

Palbociclib plus exemestane with gonadotropin-releasing hormone agonist versus capecitabine in premenopausal women with hormone receptor-positive, HER2-negative metastatic breast cancer (KCSG-BR15-10): a multicentre, open-label, randomised, phase 2 trial

BACKGROUND

Endocrine treatment is recommended by clinical guidelines as the preferred treatment option for premenopausal as well as postmenopausal women with hormone receptor-positive, HER2-negative metastatic breast cancer. In real-world clinical practice, however, a substantial number of patients are treated with chemotherapy. We aimed to compare the clinical antitumour activity and safety of palbociclib plus endocrine therapy with that of capecitabine chemotherapy in premenopausal women with hormone receptor-positive, HER2-negative metastatic breast cancer.

METHODS

This multicentre, open-label, randomised, phase 2 study was done in 14 academic institutions in South Korea. Premenopausal women aged 19 years or older with hormone receptor-positive, HER2-negative breast cancer that had relapsed or progressed during previous tamoxifen therapy and with an Eastern Cooperative Oncology Group performance status of 0-2 were included. One line of previous chemotherapy for metastatic breast cancer was allowed. Patients were randomly assigned, using a random permuted block design (with a block size of two), to receive palbociclib plus combination endocrine therapy (oral exemestane 25 mg per day for 28 days and oral palbociclib 125 mg per day for 21 days every 4 weeks plus leuprolide 3·75 mg subcutaneously every 4 weeks) or chemotherapy (oral capecitabine 1250 mg/m² twice daily for 2 weeks every 3 weeks). Randomisation was stratified by previous chemotherapy for metastatic breast cancer and visceral metastasis. The primary endpoint was progression-free survival. All analyses were done in a modified intention-to-treat population that excluded patients who did not receive study medication. This study is registered with ClinicalTrials.gov, NCT02592746, and is ongoing for follow-up of overall survival.

FINDINGS

Between June 15, 2016, and Dec 10, 2018, 189 patients were enrolled, of whom 184 were randomly assigned to the palbociclib plus endocrine therapy group (n=92) or the capecitabine group (n=92). Six patients in the capecitabine group withdrew from the study before drug administration; therefore, 92 patients in the palbociclib plus endocrine therapy group and 86 patients in the capecitabine group were included in the modified intention-to-treat analyses. 46 (50%) of 92 patients in the palbociclib plus endocrine therapy group and 45 (51%) of 92 in the capecitabine group were treatment naive for metastatic breast cancer. During a median follow-up of 17 months (IQR 9-22), median progression-free survival was 20·1 months (95% CI 14·2-21·8) in the palbociclib plus endocrine therapy group versus 14·4 months (12·1-17·0) in the capecitabine group (hazard ratio 0·659 [95% CI 0·437-0·994], one-sided log-rank p=0·0235). Treatment-related grade 3 or worse neutropenia was more common in the palbociclib plus endocrine therapy group than in the capecitabine group (69 [75%] of 92 vs 14 [16%] of 86 patients). 2 (2%) patients in the palbociclib plus endocrine therapy group and 15 (17%) patients in the capecitabine group had treatment-related serious adverse events. No treatment-related deaths occurred.

INTERPRETATION

Exemestane plus palbociclib with ovarian function suppression showed clinical benefit compared with capecitabine in terms of improved progression-free survival in premenopausal patients with hormone receptor-positive, HER2-negative metastatic breast cancer. Palbociclib plus exemestane with ovarian suppression is an active treatment option in premenopausal patients with hormone receptor-positive, HER2-negative metastatic breast cancer who have been pretreated with tamoxifen.

FUNDING

Pfizer, Shinpoong, and Daewoong Korea and Takeda.

Components of Radiologic Progressive Disease Defined by RECIST 1.1 in Patients with Metastatic Clear Cell Renal Cell Carcinoma

Background Progression-free survival (PFS) determined by Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) is the reference standard to assess efficacy of treatments in patients with clear cell renal cell carcinoma. Purpose To assess the most common components of radiologic progressive disease as defined by RECIST 1.1 in patients with clear cell renal cell carcinoma and how the progression events impact PFS. Materials and Methods This secondary analysis of the phase III METEOR trial conducted between 2013 and 2014 included patients with metastatic clear cell renal cell carcinoma, with at least one target lesion at baseline and one follow-up time point, who were determined according to RECIST 1.1 to have progressive disease. A chest, abdominal, and pelvic scan were acquired at each time point. Kruskal-Wallis analysis was used to test differences in median PFS among the RECIST 1.1 progression events. The Holm-Bonferroni method was used to compare the median PFS of the progression events for the family-wise error rate of 5% to adjust P values for multiple comparisons. Results Of the 395 patients (296 men, 98 women, and one patient with sex not reported; mean age, 61 years ± 10), 73 (18.5%) had progression due to non-target disease, 105 (26.6%) had new lesions, and 126 (31.9%) had progression of target lesions (defined by an increase in the sum of diameters). Patients with progression of non-target disease and those with new lesions had shorter PFS than patients with progression defined by the target lesions (median PFS, 2.8 months [95% confidence interval {CI}: 1.9 months, 3.7 months] and 3.6 months [95% CI: 3.3 months, 3.7 months] vs 5.4 months [95% CI: 5.0 months, 5.5 months], respectively [P < .01]). Conclusion The most common causes for radiologic progression of renal cell carcinoma were based on non-target disease and new lesions rather than change in target lesions, despite this being considered uncommon in the Response Evaluation Criteria in Solid Tumors version 1.1 literature. © RSNA, 2019 See also the editorial by Kuhl in this issue.