Volumetric Tumor Response and Progression in EGFR-mutant NSCLC Patients Treated with Erlotinib or Gefitinib

Predictive and Prognostic Factors in Melanoma Central Nervous System Metastases-A Cohort Study

BACKGROUND

Melanoma is the cancer with the highest risk of dissemination to the central nervous system (CNS), one of the leading causes of mortality from this cancer.

OBJECTIVE

To identify patients at higher risk of developing CNS metastases and to evaluate associated prognostic factors.

METHODS

A cohort study (1998-2023) assessed patients who developed CNS melanoma metastases. Multivariate logistic regression was used to identify predictive factors at melanoma diagnosis for CNS metastasis. Cox regression analysis evaluated the CNS-independent metastasis-related variables impacting survival.

RESULTS

Out of 4718 patients, 380 (8.05%) developed CNS metastases. Multivariate logistic regression showed that a higher Breslow index, mitotic rate ≥ 1 mm2, ulceration, and microscopic satellitosis were significant risk factors for CNS metastasis development. Higher patient age and the location of the primary tumor in the upper or lower extremities were protective factors. In survival analysis, post-CNS metastasis, symptomatic disease, prior non-CNS metastases, CNS debut with multiple metastases, elevated LDH levels, and leptomeningeal involvement correlated with poorer survival.

CONCLUSION

Predictive factors in the primary tumor independently associated with brain metastases include microscopic satellitosis, ulceration, higher Breslow index, and trunk location. Prognostic factors for lower survival in CNS disease include symptomatic disease, multiple CNS metastases, and previous metastases from different sites.

Lung cancer in patients who have never smoked - an emerging disease

Lung cancer is the most common cause of cancer-related deaths globally. Although smoking-related lung cancers continue to account for the majority of diagnoses, smoking rates have been decreasing for several decades. Lung cancer in individuals who have never smoked (LCINS) is estimated to be the fifth most common cause of cancer-related deaths worldwide in 2023, preferentially occurring in women and Asian populations. As smoking rates continue to decline, understanding the aetiology and features of this disease, which necessitate unique diagnostic and treatment paradigms, will be imperative. New data have provided important insights into the molecular and genomic characteristics of LCINS, which are distinct from those of smoking-associated lung cancers and directly affect treatment decisions and outcomes. Herein, we review the emerging data regarding the aetiology and features of LCINS, particularly the genetic and environmental underpinnings of this disease as well as their implications for treatment. In addition, we outline the unique diagnostic and therapeutic paradigms of LCINS and discuss future directions in identifying individuals at high risk of this disease for potential screening efforts.

Prediction Model for Tumor Volume Nadir in EGFR -mutant NSCLC Patients Treated With EGFR Tyrosine Kinase Inhibitors

PURPOSE

In patients with advanced non-small cell lung cancer (NSCLC) and oncogenic driver mutations treated with effective targeted therapy, a characteristic pattern of tumor volume dynamics with an initial regression, nadir, and subsequent regrowth is observed on serial computed tomography (CT) scans. We developed and validated a linear model to predict the tumor volume nadir in EGFR -mutant advanced NSCLC patients treated with EGFR tyrosine kinase inhibitors (TKI).

MATERIALS AND METHODS

Patients with EGFR -mutant advanced NSCLC treated with EGFR-TKI as their first EGFR-directed therapy were studied for CT tumor volume kinetics during therapy, using a previously validated CT tumor measurement technique. A linear regression model was built to predict tumor volume nadir in a training cohort of 34 patients, and then was validated in an independent cohort of 84 patients.

RESULTS

The linear model for tumor nadir prediction was obtained in the training cohort of 34 patients, which utilizes the baseline tumor volume before initiating therapy (V 0 ) to predict the volume decrease (mm 3 ) when the nadir volume (V p ) was reached: V 0 -V p =0.717×V 0 -1347 ( P =2×10 -16 ; R2 =0.916). The model was tested in the validation cohort, resulting in the R2 value of 0.953, indicating that the prediction model generalizes well to another cohort of EGFR -mutant patients treated with EGFR-TKI. Clinical variables were not significant predictors of tumor volume nadir.

CONCLUSION

The linear model was built to predict the tumor volume nadir in EGFR -mutant advanced NSCLC patients treated with EGFR-TKIs, which provide an important metrics in treatment monitoring and therapeutic decisions at nadir such as additional local abrasive therapy.

Tumor Volume Nadir in Patients With ALK-Rearranged Non-Small-Cell Lung Cancer Treated With Alectinib

PURPOSE

Patients with oncogene-driven advanced non-small-cell lung cancer (NSCLC) treated with effective targeted therapy demonstrate characteristic tumor volume dynamics with initial response, nadir, and subsequent regrowth. This study investigated tumor volume nadir and time to nadir in patients with ALK-rearranged advanced NSCLC treated with alectinib.

MATERIALS AND METHODS

In patients with advanced ALK-rearranged NSCLC treated with alectinib monotherapy, tumor volume dynamics were evaluated on serial computed tomography (CT) scans using a previously validated CT tumor measurement technique. A linear regression model was built to predict tumor volume nadir. Time-to-event analyses were performed to evaluate time to nadir.

RESULTS

Among 45 patients who experienced initial volume decrease, 37 patients (25 with tumor regrowth and 12 without regrowth but >6 months follow-up) were studied for nadir volume (V_p). The linear model to predict tumor volume nadir was built using the baseline tumor volume (V₀): V₀-V_p = .696 × V₀ + 5,326 (P < 2 × 10^-16; adjusted R² = 0.86). The percent volume changes at nadir (median, -90.9%, mean, -85.3%) showed larger decrease in patients who were treated with alectinib as first-line therapy than in the ≥2nd-line group and were independent of V₀ and clinical variables. Time to nadir had a median of 11.5 months and was longer in the first-line group (P = .04).

CONCLUSION

The tumor nadir volume in patients with ALK-rearranged advanced NSCLC treated with alectinib can be predicted by the liner regression model and consists of approximately 30% of the baseline volume minus 5 cm³, providing additional insights into precision therapy monitoring and potential guides for local ablative therapy to prolong disease control.

Tumor Growth Rate After Nadir Is Associated With Survival in Patients With EGFR-Mutant Non-Small-Cell Lung Cancer Treated With Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor

PURPOSE

To investigate the association between tumor volume growth rate after the nadir and survival in patients with EGFR-mutant advanced non-small-cell lung cancer (NSCLC) treated with erlotinib.

MATERIALS AND METHODS

Seventy-one patients with EGFR-mutant advanced NSCLC treated with erlotinib were studied for computed tomography tumor volume kinetics during therapy. The tumor growth rate after nadir was obtained using a previously published analytic module for longitudinal volume tracking to study its relationship with overall survival (OS).

RESULTS

The median tumor volume for the cohort was 19,842 mm3 at baseline and 4,083 mm3 at nadir. The median time to nadir was 6.2 months. The tumor growth rate after nadir for logeV (the natural logarithm of tumor volume measured in mm3) was 0.11/mo on average for the cohort (SE: 0.014), which was very similar to the previously validated reference value of 0.12/mo to define slow and fast tumor growth. The OS of 48 patients with slow tumor growth (≤ 0.12/mo) was significantly longer compared with 23 patients with fast tumor growth (> 0.12/mo; median OS: 37.8 v 25.0 months; P = .0012). In Cox models, tumor growth rate was also associated with survival (regression coefficient: 3.9903; P = .0024; faster rate leads to increased hazards), after adjusting for time to nadir (regression coefficient: -0.0863; P = .0008; longer time to nadir leads to decreased hazards) and smoking history.

CONCLUSION

In patients with EGFR-mutant advanced NSCLC treated with erlotinib, slower tumor growth rates after nadir were associated with longer OS, providing a rationale for using tumor growth rates to guide precision therapy for lung cancer.

Tumor Growth Rate After Nadir Is Associated With Survival in Patients With EGFR-Mutant Non-Small-Cell Lung Cancer Treated With Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor

PURPOSE

To investigate the association between tumor volume growth rate after the nadir and survival in patients with EGFR-mutant advanced non-small-cell lung cancer (NSCLC) treated with erlotinib.

MATERIALS AND METHODS

Seventy-one patients with EGFR-mutant advanced NSCLC treated with erlotinib were studied for computed tomography tumor volume kinetics during therapy. The tumor growth rate after nadir was obtained using a previously published analytic module for longitudinal volume tracking to study its relationship with overall survival (OS).

RESULTS

The median tumor volume for the cohort was 19,842 mm³ at baseline and 4,083 mm³ at nadir. The median time to nadir was 6.2 months. The tumor growth rate after nadir for log_eV (the natural logarithm of tumor volume measured in mm³) was 0.11/mo on average for the cohort (SE: 0.014), which was very similar to the previously validated reference value of 0.12/mo to define slow and fast tumor growth. The OS of 48 patients with slow tumor growth (≤ 0.12/mo) was significantly longer compared with 23 patients with fast tumor growth (> 0.12/mo; median OS: 37.8 v 25.0 months; P = .0012). In Cox models, tumor growth rate was also associated with survival (regression coefficient: 3.9903; P = .0024; faster rate leads to increased hazards), after adjusting for time to nadir (regression coefficient: -0.0863; P = .0008; longer time to nadir leads to decreased hazards) and smoking history.

CONCLUSION

In patients with EGFR-mutant advanced NSCLC treated with erlotinib, slower tumor growth rates after nadir were associated with longer OS, providing a rationale for using tumor growth rates to guide precision therapy for lung cancer.

Longitudinal Circulating Tumor DNA Analysis in Blood and Saliva for Prediction of Response to Osimertinib and Disease Progression in EGFR-Mutant Lung Adenocarcinoma

Background: We assessed whether serial ctDNA monitoring of plasma and saliva predicts response and resistance to osimertinib in EGFR-mutant lung adenocarcinoma. Three ctDNA technologies-blood-based droplet-digital PCR (ddPCR), next-generation sequencing (NGS), and saliva-based EFIRM liquid biopsy (eLB)-were employed to investigate their complementary roles. Methods: Plasma and saliva samples were collected from patients enrolled in a prospective clinical trial of osimertinib and local ablative therapy upon progression (NCT02759835). Plasma was analyzed by ddPCR and NGS. Saliva was analyzed by eLB. Results: A total of 25 patients were included. We analyzed 534 samples by ddPCR (n = 25), 256 samples by NGS (n = 24) and 371 samples by eLB (n = 22). Among 20 patients who progressed, ctDNA progression predated RECIST 1.1 progression by a median of 118 days (range: 61-272 days) in 11 (55%) patients. Of nine patients without ctDNA progression by ddPCR, two patients had an increase in mutant EGFR by eLB and two patients were found to have ctDNA progression by NGS. Levels of ctDNA measured by ddPCR and NGS at early time points, but not volumetric tumor burden, were associated with PFS. EGFR/ERBB2/MET/KRAS amplifications, EGFR C797S, PIK3CA E545K, PTEN V9del, and CTNNB1 S45P were key resistance mechanisms identified by NGS. Conclusion: Serial assessment of ctDNA in plasma and saliva predicts response and resistance to osimertinib, with each assay having supplementary roles.

Radiogenomics in brain, breast, and lung cancer: opportunities and challenges

The field of radiogenomics largely focuses on developing imaging surrogates for genomic signatures and integrating imaging, genomic, and molecular data to develop combined personalized biomarkers for characterizing various diseases. Our study aims to highlight the current state-of-the-art and the role of radiogenomics in cancer research, focusing mainly on solid tumors, and is broadly divided into four sections. The first section reviews representative studies that establish the biologic basis of radiomic signatures using gene expression and molecular profiling information. The second section includes studies that aim to non-invasively predict molecular subtypes of tumors using radiomic signatures. The third section reviews studies that evaluate the potential to augment the performance of established prognostic signatures by combining complementary information encoded by radiomic and genomic signatures derived from cancer tumors. The fourth section includes studies that focus on ascertaining the biological significance of radiomic phenotypes. We conclude by discussing current challenges and opportunities in the field, such as the importance of coordination between imaging device manufacturers, regulatory organizations, health care providers, pharmaceutical companies, academic institutions, and physicians for the effective standardization of the results from radiogenomic signatures and for the potential use of these findings to improve precision care for cancer patients.

Collagen modifying enzyme P4HA1 is overexpressed and plays a role in lung adenocarcinoma

Lung cancer is the leading cause of cancer-related deaths globally and is histologically defined as either small cell lung cancer (SCLC) or non-small cell lung cancer (NSCLC), with the latter accounting for 80% of all lung cancers. The 5-year overall survival rate for lung cancer patients is low as it is often discovered at advanced stages when potential cure by surgical resection is no longer an option. To identify a biomarker and target for lung cancer, we performed analysis of multiple datasets of lung cancer gene expression data. Our analyses indicated that the collagen-modifying enzyme Prolyl 4-Hydroxylase Subunit Alpha 1 (P4HA1) is overexpressed in NSCLC. Furthermore, our investigation found that overexpression of enzymes involved in this pathway predicts poor outcome for patients with lung adenocarcinoma. Our functional studies using knockdown strategies in lung cancer cell lines in vitro indicated that P4HA1 is critical for lung cancer growth, migration, and invasion. Additionally, diethyl pythiDC (PythiDC), a small molecule inhibitor, decreased the malignant phenotypes of lung cancer cells. Moreover, we found that miR-124 regulates and targets P4HA1 in lung cancer cells. Thus, our study suggests that collagen-modifying enzymes play an important role in lung cancer aggressiveness. Furthermore, our studies showed that P4HA1 is required for lung cancer cell growth and invasion, suggesting its potential as a valid therapeutic target in lung adenocarcinoma.

A Model-Strengthened Imaging Biomarker for Survival Prediction in EGFR-Mutated Non-small-cell Lung Carcinoma Patients Treated with Tyrosine Kinase Inhibitors

Non-small-cell lung carcinoma is a frequent type of lung cancer with a bad prognosis. Depending on the stage and genomics, several therapeutical approaches are used. Tyrosine Kinase Inhibitors (TKI) may be successful for a time in the treatment of EGFR-mutated non-small cells lung carcinoma. Our objective is here to introduce a survival assessment as their efficacy in the long run is challenging to evaluate. The study includes 17 patients diagnosed with EGFR-mutated non-small cell lung cancer and exposed to an EGFR-targeting TKI with 3 computed tomography (CT) scans of the primary tumor (one before the TKI introduction and two after). An imaging biomarker based on evolution of texture heterogeneity between the first and the third exams is derived and computed from a mathematical model and patient data. Defining the overall survival as the time between the introduction of the TKI treatment and the patient death, we obtain a statistically significant correlation between the overall survival and our imaging marker ([Formula: see text]). Using the ROC curve, the patients are separated into two populations and the comparison of the survival curves is statistically significant ([Formula: see text]). The baseline exam seems to have a significant role in the prediction of response to TKI treatment. More precisely, our imaging biomarker defined using only the CT scan before the TKI introduction allows to determine a first classification of the population which is improved over time using the imaging marker as soon as more CT scans are available. This exploratory study leads us to think that it is possible to obtain a survival assessment using only few CT scans of the primary tumor.

Tumor Volume Analysis as a Predictive Marker for Prolonged Survival in Anaplastic Lymphoma Kinase-rearranged Advanced Non-Small Cell Lung Cancer Patients Treated With Crizotinib

PURPOSE

Targeted inhibition of anaplastic lymphoma kinase (ALK) has been widely used for the treatment of advanced non-small cell lung cancer (NSCLC) with ALK rearrangements. We performed tumor volume analysis of ALK-rearranged advanced NSCLC treated with crizotinib to identify an early predictive marker for prolonged survival.

MATERIALS AND METHODS

Cases of 42 patients with ALK-rearranged advanced NSCLC (16 men, 26 women; median age: 55.7 y) treated with crizotinib as their first ALK-directed therapy were retrospectively studied. Tumor volume measurements of dominant lung lesions were performed on baseline computed tomography and follow-up computed tomography at 8 weeks of therapy. The relationships between the 8-week volume change (%) and overall survival (OS) were investigated.

RESULTS

The 8-week tumor volume change ranged from -99.3% to 117.5% (median: -57.7%). Using the 25th percentile of the 8-week volume change of -74%, 11 patients with >74% volume decrease at 8 weeks had a significantly longer OS compared with 31 patients with ≤74% decrease (median OS: 92.0 vs. 22.8 mo; P=0.0048). In multivariable analyses using Cox proportional hazards models, the 8-week volume decrease of >74% was significantly associated with longer OS (hazard ratio=0.14, 95% confidence interval: 0.03-0.59; Cox P=0.008) after adjusting for tumor stage (stage IV vs. recurrent NSCLC, hazard ratio=5.6, 95% confidence interval: 1.29-24.3; P=0.02).

CONCLUSIONS

The 8-week tumor volume decrease of >74% is significantly associated with longer OS in patients with ALK-rearranged NSCLC treated with crizotinib.

Tumor volume dynamics and tumor growth rate in ALK-rearranged advanced non-small-cell lung cancer treated with crizotinib

Purpose

The purpose of the study is to investigate volumetric tumor burden dynamics and tumor growth rates in ALK-rearranged advanced NSCLC patients during crizotinib monotherapy.

Methods

The study included 44 ALK-rearranged advanced NSCLC patients treated with crizotinib monotherapy as their initial ALK-directed therapy, who had at least one measurable lung lesion and at least two follow-up CT scans, and experienced tumor volume increase while on crizotinib. The tumor volume (in mm³) of the dominant lung lesion was measured on serial CT scans during therapy for analysis of tumor growth rates after the volume nadir.

Results

A total of 231 volume measurements from the nadir to the end of crizotinib therapy or the last follow-up in 44 patients were analyzed in a linear mixed-effects model, fitting time (in months since baseline) as a random effect. When measured from the volume nadir, the tumor growth rate of the logarithm of tumor volume (log_eV) was 0.04/month (SE = 0.012, P = 0.0011) in the unadjusted model. When adjusted for the baseline volume (log_eV₀), the growth rate was again 0.04/month (SE = 0.011, P = 0.0004). When adjusted for clinical variables and log_eV₀, the growth rate was 0.045/month (SE = 0.012, P = 0.0002), indicating that the tumor growth rate after nadir in this cohort remains very close to 0.04/month regardless of log_eV₀ or clinical factors.

Conclusions

Tumor volume growth rate after nadir in ALK-rearranged NSCLC patients treated with crizotinib was obtained, providing objective reference values that can inform physicians when deciding to keep their patients on ALK directed therapy with slowly progressing lung cancer.

Correlation between initial tumour volume and treatment duration on Dabrafenib: observation study of subjects with BRAF mutant melanoma on the BRF112680 trial

BACKGROUND

Planar-based measurements of lesions in metastatic melanoma have limitations in estimating tumor burden of a patient and in predicting response to treatment. Volumetric imaging might add predictive value to Response criteria in Solid Tumor (RECIST)-measurement. Based on clinical observations, we explored the association between baseline tumor volume (TV) and duration of treatment with dabrafenib in patients with metastatic melanoma. We have also explored the prognostic value of TV for overall survival (OS) and progression free survival (PFS).

METHODS

This is a retrospective, chart-review of primary source documents and medical imaging of a cohort of patients participating in the BRF112680 phase 1 clinical trial at the Prince of Wales Hospital. TV was quantified by contouring all the measurable baseline target lesions in the standard manner for radiation planning using Voxxar™ software. We used Cox regression models to analyse associations between TV and duration of treatment with dabrafenib and between TV, PFS and OS.

RESULTS

Among 13 patients of BRAF 112680 trial, 10 were included in the retrospective analysis. Target lesion sum volume ranged from 0.3 to 1065.5 cm³ (cc), with a median of 27.5 cc. The median PFS and OS were 420 days (range 109-1765) and 1680 days (range 390-2940), respectively. The initial TV was inversely correlated with duration of treatment with dabrafenib (rho - 0.6; P 0.03). In multivariate analysis, TV was a predictor for OS (HR 2.81 CI 1.06-6.19) and PFS (8.76 (CI 1.05-43.58). Patients with tumour volume above the median had significantly lower OS of 6-months compared to 56-months survival for patients with smaller volumes; P = 0.019.

CONCLUSIONS

TV is a predictor for treatment duration and is prognostic of OS and PFS in patients with metastatic melanoma. These findings need to be validated prospectively in clinical trials.

Measurement Variability in Treatment Response Determination for Non-Small Cell Lung Cancer: Improvements Using Radiomics

Multimodality imaging measurements of treatment response are critical for clinical practice, oncology trials, and the evaluation of new treatment modalities. The current standard for determining treatment response in non-small cell lung cancer (NSCLC) is based on tumor size using the RECIST criteria. Molecular targeted agents and immunotherapies often cause morphological change without reduction of tumor size. Therefore, it is difficult to evaluate therapeutic response by conventional methods. Radiomics is the study of cancer imaging features that are extracted using machine learning and other semantic features. This method can provide comprehensive information on tumor phenotypes and can be used to assess therapeutic response in this new age of immunotherapy. Delta radiomics, which evaluates the longitudinal changes in radiomics features, shows potential in gauging treatment response in NSCLC. It is well known that quantitative measurement methods may be subject to substantial variability due to differences in technical factors and require standardization. In this review, we describe measurement variability in the evaluation of NSCLC and the emerging role of radiomics.

Hyper-progressive disease in a patient with advanced non-small cell lung cancer on immune checkpoint inhibitor therapy: A case report and literature review

OBJECTIVES

While immune checkpoint inhibitor (ICI) therapy has excellent efficacy in treating multiple cancers, some patients experience accelerated disease progression, defined as hyper-progressive disease (HPD). However, the characteristics of HPD, especially in patients with non-small-cell lung cancer (NSCLC), remain to be elucidated.

MATERIALS AND METHODS

We report about an advanced NSCLC patient with striking disease progression, defined as HPD by existing standards, after the administration of pembrolizumab. We also reviewed related studies to discuss the definition, relative factors, and prognosis of HPD.

RESULTS AND CONCLUSION

This case of NSCLC with HPD had a series of characteristics not widely described in HPD cases previously reported, suggesting the potential complexity of this phenomenon and the necessity to study its characteristics and to more closely monitor patients who are administered ICIs.

Imaging of Precision Therapy for Lung Cancer: Current State of the Art

Advances in characterization of molecular and genomic abnormalities specific to lung cancer have made precision therapy the current standard of care for lung cancer treatment. This article will provide a cutting-edge review of imaging of lung cancer in the current era of precision medicine. The focus of the article includes (a) an update on the recent advances in precision therapy for non-small cell lung cancer and their implications on imaging; (b) molecular and genomic biomarkers and pitfalls of image interpretations for lung cancer precision therapy; and (c) review of the current approaches and future directions of precision imaging for lung cancer, emphasizing emerging observations in longitudinal tumor kinetics, radiomics, and molecular and functional imaging. The article is designed to help radiologists to remain up to date in the rapidly evolving world of lung cancer therapy and serve as key members of multidisciplinary teams caring for these patients.

Incidence and prognosis of brain metastases in cutaneous melanoma patients: a population-based study

Brain metastases (BM) from cutaneous melanoma are associated with poor prognosis. Population-based data describing the associated factors of incidence and prognosis of BM from melanoma are still lacking. We identified 121 255 melanoma patients diagnosed during 2010-2015 from the Surveillance, Epidemiology, and End Results program, and identified predictive factors for incidence and survival of BM patients by using multivariable logistic and Cox's proportional hazard regression, respectively. We identified 1547 patients with BM at the time of diagnosis of malignant cutaneous melanoma, representing 1.3% of the entire cohort and 35.4% of the subset with metastatic disease. The characteristics associated with higher BM incidence were male sex, age 40-60 years, melanoma location of face/head/neck, histologic type of nodular, higher T-stage, ulceration and extracranial metastases. The median overall survival and median cutaneous melanoma specific survival of patients with BM was 5 and 6 months, respectively. The relative factors of poor survival were older age and more extracranial metastatic sites. In summary, we provided insight into the epidemiology of BM from cutaneous melanoma. These results may provide significant help to improve the screening strategy of BM strategy and update the existing prognosis evaluation system.

Tumor Response Assessment for Precision Cancer Therapy: Response Evaluation Criteria in Solid Tumors and Beyond

Objective assessment of tumor responses and treatment results has been the basis for the advancement of cancer therapies, and imaging plays a key role to provide a "common language" to describe the results of cancer treatment. Although Response Evaluation Criteria in Solid Tumors (RECIST) has been the most widely accepted method for assessing tumor response in the past decades, the limitations of RECIST have increasingly becoming recognized, especially with the recent advances of precision-medicine approaches to cancer. This article reviews the current concept of tumor response evaluations based on RECIST, describes the limitations of RECIST, and proposes strategies to overcome the limitations. The article emphasizes specific limitations in the setting of precision cancer therapy and cancer immunotherapy and discusses the important insights provided by the cutting-edge investigations in the emerging fields.

Automated image analysis tool for tumor volume growth rate to guide precision cancer therapy: EGFR-mutant non-small-cell lung cancer as a paradigm

PURPOSE

To develop an automated analytic module for calculation of tumor growth rate from serial CT scans and to apply the module and evaluate reproducibility in a pilot cohort of advanced NSCLC patients with EGFR mutations treated with EGFR tyrosine kinase inhibitors.

MATERIALS AND METHODS

The module utilized a commercially available image-processing workstation equipped with a validated tumor volume measurement tool. An automated analytic software module was programmed with the capability to record and display serial tumor volume changes and to calculate tumor volume growth rate over time and added to the workstation. The module was applied to evaluate the tumor growth rate in a pilot cohort of 24 EGFR-mutant patients treated with EGFR inhibitors, and reproducibility references as tested by two independent thoracic radiologists.

RESULTS

The module analyzed chest CT scans from 24 patients (5 males, 19 females; median age: 61) with a median of 8 scans per patient, totaling 227 scans and provided a graphical display with an automated and instant calculation of tumor growth rate after the nadir volume for each patient. High inter and intraobserver agreements were noted for tumor growth rates, with concordance correlation coefficients of 0.9323 and 0.9668, respectively. Interpretation of slow versus fast tumor growth using previously identified threshold of ≤0.15/month had a perfect interobserver agreement (κ = 1.00), and an excellent intraobserver agreement (κ = 0.895).

CONCLUSIONS

The present study describes the development of an image analytic module for assessing tumor growth rate and the data demonstrates the functionality and reproducibility of the module in a pilot cohort of EGFR-mutant NSCLC patients treated with EGFR-TKI. The image analytic module is an initial step for clinical translation of the tumor growth rate approach to guide cancer treatment in precision oncology.

Best Response According to RECIST During First-line EGFR-TKI Treatment Predicts Survival in EGFR Mutation-positive Non-Small-cell Lung Cancer Patients

INTRODUCTION

The association between the response to first-line epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) and survival in EGFR mutation-positive non-small-cell lung cancer (NSCLC) remains unclear. We studied the association between the response to first-line EGFR-TKIs and survival using Response Evaluation Criteria In Solid Tumors (RECIST) and maximal tumor shrinkage.

MATERIALS AND METHODS

We analyzed data from patients with advanced EGFR mutation-positive NSCLC enrolled in first-line gefitinib and afatinib trials. A total of 98 patients who achieved a response or stable disease and had ≥ 1 measurable target lesion were included. The association between the best response by RECIST or maximal tumor shrinkage and survival was analyzed in Kaplan-Meier and Cox regression models with the landmark method. The specified landmark time points were 8 weeks, the median time to maximal tumor shrinkage (16.5 weeks), and median progression-free survival (PFS; 56 weeks).

RESULTS

A total of 76 patients (77%) responded to gefitinib or afatinib. Of these 76 patients, 49 (64%) and 75 (99%) had achieved a response at 8 and 16.5 weeks, respectively. All responders had achieved a response by 56 weeks. The responders had a significantly longer PFS and overall survival (OS) compared with those with stable disease at 16.5 weeks (PFS, P = .003; OS, P < .001) and 56 weeks (PFS, P = .026; OS, P = .016) but not at 8 weeks (PFS, P = .104; OS, P = .313). Among the responders, greater tumor shrinkage was not associated with longer PFS or OS.

CONCLUSION

Those with a response to first-line gefitinib or afatinib had more favorable PFS and OS compared with those with stable disease. A sufficient observation period was required for the response to occur and predict outcomes. Greater maximal tumor shrinkage in the responders was not predictive of survival.

Tumor Response Dynamics of Advanced Non-small Cell Lung Cancer Patients Treated with PD-1 Inhibitors: Imaging Markers for Treatment Outcome

Purpose: We evaluated tumor burden dynamics in patients with advanced non-small cell lung cancer (NSCLC) treated with commercial PD-1 inhibitors to identify imaging markers associated with improved overall survival (OS).Experimental Design: The study included 160 patients with advanced NSCLC treated with commercial nivolumab or pembrolizumab monotherapy as a part of clinical care. Tumor burden dynamics were studied for the association with OS.Results: Tumor burden change at best overall response (BOR) ranged from -100% to +278% (median, +3.5%). Response rate (RR) was 18% (29/160). Current and former smokers had a higher RR than never smokers (P = 0.04). Durable disease control for at least 6 months was noted in 26 patients (16%), which included 10 patients with stable disease as BOR. Using a landmark analysis, patients with <20% tumor burden increase from baseline within 8 weeks of therapy had longer OS than patients with ≥20% increase (median OS, 12.4 vs. 4.6 months, P < 0.001). Patients with <20% tumor burden increase throughout therapy had significantly reduced hazards of death (HR, 0.24; Cox P < 0.0001) after adjusting for smoking (HR, 0.86; P = 0.61) and baseline tumor burden (HR, 1.55; P = 0.062), even though some patients met criteria for RECIST progression while on therapy. One patient (0.6%) had atypical response pattern consistent with pseudoprogression.Conclusions: Objective response or durable disease control was noted in 24% of patients with advanced NSCLC treated with commercial PD-1 inhibitors. A tumor burden increase of <20% from baseline during therapy was associated with longer OS, proposing a practical marker of treatment benefit. Pseudoprogression is rare in NSCLCs treated with PD-1 inhibitors. Clin Cancer Res; 23(19); 5737-44. ©2017 AACR.

Monitoring immune-checkpoint blockade: response evaluation and biomarker development

Cancer immunotherapy using immune-checkpoint blockade (ICB) has created a paradigm shift in the treatment of advanced-stage cancers. The promising antitumour activity of monoclonal antibodies targeting the immune-checkpoint proteins CTLA-4, PD-1, and PD-L1 led to regulatory approvals of these agents for the treatment of a variety of malignancies. Patients might experience clinical benefits from treatment with these agents, despite unconventional patterns of tumour response that can be misinterpreted as disease progression, warranting a new, specific approach to evaluate responses to immunotherapy. In addition, biomarkers that can predict responsiveness to ICB are being extensively investigated to further advance precision immunotherapy. Herein, we review the biological mechanisms underlying the unconventional response patterns associated with ICB, describe strategies for the objective assessments of such responses, and also highlight the ongoing efforts to identify biomarkers, in order to guide treatment with ICB. We provide state-of-the-art knowledge of immune-related response evaluations, identify unmet needs requiring further investigations, and propose future directions to maximize the benefits of ICB therapy.

Pharmacometric Modeling of Liver Metastases' Diameter, Volume, and Density and Their Relation to Clinical Outcome in Imatinib-Treated Patients With Gastrointestinal Stromal Tumors

Three‐dimensional and density‐based tumor metrics have been suggested to better discriminate tumor response to treatment than unidimensional metrics, particularly for tumors exhibiting nonuniform size changes. In the developed pharmacometric modeling framework based on data from 77 imatinib‐treated gastrointestinal patients, the time‐courses of liver metastases' maximum transaxial diameters, software‐calculated actual volumes (V_actual) and calculated ellipsoidal volumes were characterized by logistic growth models, in which imatinib induced a linear dose‐dependent size reduction. An indirect response model best described the reduction in density. Substantial interindividual variability in the drug effect of all response assessments and additional interlesion variability in the drug effect on density were identified. The predictive ability of longitudinal tumor unidimensional and three‐dimensional size and density on overall survival (OS) and progression‐free survival (PFS) were compared using parametric time‐to‐event models. Death hazard increased with increasing V_actual. This framework may guide early clinical interventions based on three‐dimensional tumor responses to enhance benefits for patients with gastrointestinal stromal tumors (GIST).

Radiogenomic Analysis of Oncological Data: A Technical Survey

In the last few years, biomedical research has been boosted by the technological development of analytical instrumentation generating a large volume of data. Such information has increased in complexity from basic (i.e., blood samples) to extensive sets encompassing many aspects of a subject phenotype, and now rapidly extending into genetic and, more recently, radiomic information. Radiogenomics integrates both aspects, investigating the relationship between imaging features and gene expression. From a methodological point of view, radiogenomics takes advantage of non-conventional data analysis techniques that reveal meaningful information for decision-support in cancer diagnosis and treatment. This survey is aimed to review the state-of-the-art techniques employed in radiomics and genomics with special focus on analysis methods based on molecular and multimodal probes. The impact of single and combined techniques will be discussed in light of their suitability in correlation and predictive studies of specific oncologic diseases.

Molecular Targeted Therapy in Modern Oncology: Imaging Assessment of Treatment Response and Toxicities

Oncology is a rapidly evolving field with a shift toward personalized cancer treatment. The use of therapies targeted to the molecular features of individual tumors and the tumor microenvironment has become much more common. In this review, anti-angiogenic and other molecular targeted therapies are discussed, with a focus on typical and atypical response patterns and imaging manifestations of drug toxicities.

Strategies in functional proteomics: Unveiling the pathways to precision oncology

Personalised strategies in cancer care are required to overcome the therapeutic challenges posed by variability between patients and disease subsets. To this end, enhanced precision tools must be developed to describe the molecular drivers of malignant proliferation. Such tools must also identify druggable targets and biomarkers in order to provide essential information regarding drug development and therapeutic outcome. Here we discuss how proteomics-based approaches provide a set of viable methodologies capable of delivering quantitative information throughout the main stages of personalised oncology and a ratiometric platform that delivers systems-wide methods for drug evaluation.

Systemic and Tumor Th1 and Th2 Inflammatory Profile and Macrophages in Lung Cancer: Influence of Underlying Chronic Respiratory Disease

INTRODUCTION

Chronic respiratory conditions, especially chronic obstructive pulmonary disease (COPD), and inflammatory events underlie lung cancer (LC). We hypothesized that profiles of T helper 1 and T helper 2 cytokines and type 1 and type 2 macrophages (M1 and M2) are differentially expressed in lung tumors and blood of patients with NSCLC with and without COPD and that the ratio M1/M2 specifically may influence their survival.

METHODS

In blood, inflammatory cytokines (determined by enzyme-linked immunosorbent assay) were quantified in 80 patients with LC (60 with LC and COPD [the LC-COPD group] and 20 with LC only [the LC-only group]) and lung specimens (tumor and nontumor) from those undergoing thoracotomy (20 in the LC-COPD group and 20 in the LC-only group).

RESULTS

In the LC-COPD group compared with in the LC-only group, systemic levels of tumor necrosis factor-α, interleukin-2 (IL-2), transforming growth factor-β, and IL-10 were increased, whereas vascular endothelial growth factor and IL-4 levels were decreased. In lung tumors, levels of tumor necrosis factor-α, transforming growth factor-β, and IL-10 were higher than in nontumor parenchyma in the LC-COPD group, whereas IL-2 and vascular endothelial growth factor levels were higher in tumors of both the LC-only and LC-COPD groups. Compared with in nontumor lung, M1 macrophage counts were reduced whereas M2 counts were increased in tumors of both patient groups, and the M1/M2 ratio was higher in the LC-COPD group than the LC-only group. M1 and M2 counts did not influence patients' survival.

CONCLUSIONS

The relative predominance of T helper 1 cytokines and M1 macrophages in the blood and tumors of patients with underlying COPD imply that a stronger proinflammatory pattern exists in these patients. Inflammation should not be targeted systematically in all patients with LC. Screening for the presence of underlying respiratory diseases and identification of the specific inflammatory pattern should be carried out in patients with LC, at least in early stages of their disease.