Addressing challenges in low-income and middle-income countries through novel radiotherapy research opportunities.

Although radiotherapy continues to evolve as a mainstay of the oncological armamentarium, research and innovation in radiotherapy in low-income and middle-income countries (LMICs) faces challenges. This third Series paper examines the current state of LMIC radiotherapy research and provides new data from a 2022 survey undertaken by the International Atomic Energy Agency and new data on funding. In the context of LMIC-related challenges and impediments, we explore several developments and advances-such as deep phenotyping, real-time targeting, and artificial intelligence-to flag specific opportunities with applicability and relevance for resource-constrained settings. Given the pressing nature of cancer in LMICs, we also highlight some best practices and address the broader need to develop the research workforce of the future. This Series paper thereby serves as a resource for radiation professionals.

Pretreatment PET/CT imaging of angiogenesis based on 18F-RGD tracer uptake may predict antiangiogenic response.

PURPOSE: To explore the relationship between metabolic uptake of the 18F-ALF-NOTA-PRGD2 (18F-RGD) tracer on positron emission tomography/computerized tomography (PET/CT) and the antiangiogenic effect of apatinib in patients with solid malignancies. MATERIALS AND PATIENTS: Patients with measurable lesions scheduled for second- or third-line single-agent therapy with apatinib were eligible for this prospective clinical trial. All patients underwent 18F-RGD PET/CT examination before the start of treatment. Standardized uptake values (SUVs) of contoured tumor lesions were computed and compared using independent sample t-tests or the Mann-Whitney U test. Receiver-operating characteristic (ROC) curve analysis was used to determine accuracy in predicting response. Survival curves were compared using the Kaplan-Meier method. RESULTS: Of 38 patients who consented to study participation, 25 patients with 42 measurable lesions met the criteria for inclusion in this response assessment analysis. The median follow-up time was 3 months (range, 1-10 months), and the median progression-free survival (PFS) was 3 months (95% confidence interval, 1.04-4.96). The SUVpeak and SUVmean were significantly higher in responding tumors than in non-responding tumors (4.98 ± 2.34 vs 3.59 ± 1.44, p = 0.048; 3.71 ± 1.15 vs 2.95 ± 0.49, P = 0.036). SUVmax did not differ between responding tumors and non-responding tumors (6.58 ± 3.33 vs 4.74 ± 1.83, P = 0.078). An exploratory ROC curve analysis indicated that SUVmean [area under the ROC curve (AUC) = 0.700] was a better parameter than SUVpeak (AUC = 0.689) for predicting response. Using a threshold value of 3.82, high SUVmean at baseline was associated with improved PFS (5.0 vs. 3.4 months, log-rank P = 0.036). CONCLUSION: 18F-RGD uptake on PET/CT imaging pretreatment may predict the response to antiangiogenic therapy, with higher 18F-RGD uptake in tumors predicting a better response to apatinib therapy.

Personalized Radiation Therapy (PRT) for Lung Cancer.

This chapter reviews and discusses approaches and strategies of personalized radiation therapy (PRT) for lung cancers at four different levels: (1) clinically established PRT based on a patient's histology, stage, tumor volume and tumor locations; (2) personalized adaptive radiation therapy (RT) based on image response during treatment; (3) PRT based on biomarkers; (4) personalized fractionation schedule. The current RT practice for lung cancer is partially individualized according to tumor histology, stage, size/location, and combination with use of systemic therapy. During-RT PET-CT image guided adaptive treatment is being tested in a multicenter trial. Treatment response detected by the during-RT images may also provide a strategy to further personalize the remaining treatment. Research on biomarker-guided PRT is ongoing. The biomarkers include genomics, proteomics, microRNA, cytokines, metabolomics from tumor and blood samples, and radiomics from PET, CT, SPECT images. Finally, RT fractionation schedule may also be personalized to each individual patient to maximize therapeutic gain. Future PRT should be based on comprehensive considerations of knowledge acquired from all these levels, as well as consideration of the societal value such as cost and effectiveness.

Treatment-Related Pneumonitis of EGFR Tyrosine Kinase Inhibitors Plus Thoracic Radiation Therapy in Patients With Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis.

Thoracic radiation therapy (RT) for non-small cell lung cancers may overcome resistance to tyrosine kinase inhibitors (TKIs). However, the risk of severe treatment-related pneumonitis (TRP) is a major concern, and the results of the combined treatment remain controversial. Therefore, we aimed to systematically review existing publications and provide a meta-analysis of TRP from a combined therapy of thoracic RT and TKIs. A systematic literature review was performed using the PubMed-MEDLINE and Embase databases to identify eligible publications. The number of severe TRP cases of grade 3 or higher was extracted and then analyzed by fixed or randomized model meta-analysis. Heterogeneity tests were performed using the I² and τ² statistics. Subgroup analyses were conducted on the types of RT and the sequence of the combined treatment. Our literature search identified 37 eligible studies with 1143 patients. Severe TRP occurred in 3.8% (95% CI, 1.8%-6.5%) of patients overall, and fatal pneumonitis occurred rarely in 0.1% (95% CI, 0.0%-0.3%). In the subgroup analysis, the severe TRP proportion was 2.3% (95% CI, 1.0%-4.1%) for patients under definitive (chemo)RT (19 studies, n = 702) versus 2.9% (95% CI, 1.3%-5.1%) for patients who received local stereotactic body RT or palliative RT (15 studies, n = 361). The severe TRP rate was 4.9% (95% CI, 2.4%-8.1%) for concurrent TKI and RT (26 studies, n = 765), which was significantly higher than TRP of 0.4% (95% CI, 0.0%-3.1%) for sequential therapy (6 studies, n = 200). Our meta-analysis showed that combined thoracic RT and epidermal growth factor receptor-TKI therapy has an acceptable risk of severe TRP and rare mortality in patients with non-small cell lung cancers. Concurrent treatment is less tolerable and should be administered with caution. Further investigations using osimertinib are required as the data on its effects are limited.

Hypofractionated Stereotactic Radiation Therapy Dosimetric Tolerances for the Inferior Aspect of the Brachial Plexus: A Systematic Review.

We sought to systematically review and summarize dosimetric factors associated with radiation-induced brachial plexopathy (RIBP) after stereotactic body radiation therapy (SBRT) or hypofractionated image guided radiation therapy (HIGRT). From published studies identified from searches of PubMed and Embase databases, data quantifying risks of RIBP after 1- to 10-fraction SBRT/HIGRT were extracted and summarized. Published studies have reported <10% risks of RIBP with maximum doses (Dmax) to the inferior aspect of the brachial plexus of 32 Gy in 5 fractions and 25 Gy in 3 fractions. For 10-fraction HIGRT, risks of RIBP appear to be low with Dmax < 40 to 50 Gy. For a given dose value, greater risks are anticipated with point volume-based metrics (ie, D0.03-0.035cc: minimum dose to hottest 0.03-0.035 cc) versus Dmax. With SBRT/HIGRT, there were insufficient published data to predict risks of RIBP relative to brachial plexus dose-volume exposure. Minimizing maximum doses and possibly volume exposure of the brachial plexus can reduce risks of RIBP after SBRT/HIGRT. Further study is needed to better understand the effect of volume exposure on the brachial plexus and whether there are location-specific susceptibilities along or within the brachial plexus structure.

Clinical factors and major pathological response after neoadjuvant chemoimmunotherapy in potentially resectable lung squamous cell carcinoma.

Objective: Major pathological response (MPR) helps evaluate the prognosis of patients with lung squamous cell carcinoma (LUSC). However, the clinical factors that affect the achievement of MPR after neoadjuvant chemoimmunotherapy (NCIO) in patients with LUSC remain unclear. This study aimed to explore the clinical factors affecting the MPR after NCIO in patients with potentially resectable LUSC. Methods: This retrospective study included patients with stage IIB-IIIC LUSC who underwent surgical resection after receiving NCIO at a center between March 2020 and November 2022. In addition to the postoperative pathological remission rate, sex, age, body mass index (BMI), smoking history, TNM stage, hematological and imaging test results, and other indicators were examined before NCIO. According to the pathological response rate of the surgically removed tumor tissue, the patients were split into MPR and non-MPR groups. Results: In total, 91 LUSC patients who met the study's eligibility criteria were enrolled: 32 (35%) patients in the non-MPR group and 59 (65%) in the MPR group, which included 43 cases of pathological complete remission (pCR). Pre-treatment lymphocyte level (LY) (odds ratio [OR] =5.997), tumor burden (OR=0.958), N classification (OR=15.915), radiographic response (OR=11.590), pulmonary atelectasis (OR=5.413), and PD-L1 expression (OR=1.028) were independently associated with MPR (all P < 0.05). Based on these six independent predictors, we developed a nomogram model of prediction having an area under the curve (AUC) of 0.914 that is simple to apply clinically to predict the MPR. The MPR group showed greater disease-free survival (DFS) than the non-MPR group, according to the survival analysis (P < 0.001). Conclusion: The MPR rate of NCIO for potentially resectable LUSC was 65%. LY, tumor burden, N classification, radiographic response, pulmonary atelectasis, and PD-L1 expression in patients with LUSC before NCIO were the independent and ideal predictors of MPR. The developed nomogram demonstrated a good degree of accuracy and resilience in predicting the MPR following NCIO, indicating that it is a useful tool for assuring customized therapy for patients with possibly resectable LUSC.

Survival Outcome Analysis of Stereotactic Body Radiotherapy and Immunotherapy (SBRT-IO) versus SBRT-Alone in Unresectable Hepatocellular Carcinoma.

Introduction: While combination of stereotactic body radiotherapy (SBRT) and immunotherapy are promising, their efficacy and safety have not been compared with SBRT-alone in patients with unresectable hepatocellular carcinoma (HCC). Methods: This retrospective study included 100 patients with nonmetastatic, unresectable HCC in two hospitals. Eligible patients had tumor nodules ≤3 and Child-Pugh liver function score of A5 to B7. Seventy patients received SBRT-alone, and 30 patients underwent combined SBRT and immunotherapy (SBRT-IO). Overall survival (OS), time to progression (TTP), overall response rate (ORR), and toxicity were analyzed. We adjusted for the potential confounding factors using propensity score matching. Results: The median tumor size was 7.3 cm (range, 2.6-18 cm). Twenty-five (25%) of patients had vascular invasion. Before propensity score matching, the 1-year and 3-year OS rate was 89.9% and 59.8% in the SBRT-IO group and 75.7% and 42.3% in SBRT-alone group (p = 0.039). After propensity score matching (1:2), 25 and 50 patients were selected from the SBRT-IO and SBRT-alone group. The 1-year and 3-year OS was 92.0% and 63.9% in the SBRT-IO group versus 74.0% and 43.3% in the SBRT-alone group (p = 0.034). The 1-year and 3-year TTP was better in SBRT-IO group (1-year: 68.9% vs. 58.9% and 3-year: 61.3% vs. 32.5%, p = 0.057). The ORR of 88% (complete response [CR]: 56%, partial response [PR]: 22%) in SBRT-IO arm was significantly better than 50% (CR: 20%, PR: 30%) in the SBRT-alone arm (p = 0.006). Three patients (12%) developed ≥grade 3 immune-related treatment adverse events (n = 2 hepatitis, n = 1 dermatitis) leading to permanent treatment discontinuation. Conclusion: Adding immunotherapy to SBRT resulted in better survival with manageable toxicities. Prospective randomized trial is warranted.

Thymomas and thymic carcinomas: Clinical Practice Guidelines in Oncology.

Masses in the anterior mediastinum can be neoplasms (eg, thymomas, thymic carcinomas, or lung metastases) or non-neoplastic conditions (eg, intrathoracic goiter). Thymomas are the most common primary tumor in the anterior mediastinum, although they are rare. Thymic carcinomas are very rare. Thymomas and thymic carcinomas originate in the thymus. Although thymomas can spread locally, they are much less invasive than thymic carcinomas. Patients with thymomas have 5-year survival rates of approximately 78%. However, 5-year survival rates for thymic carcinomas are only approximately 40%. These guidelines outline the evaluation, treatment, and management of these mediastinal tumors.

Non-small cell lung cancer, version 2.2013.

These NCCN Guidelines Insights focus on the diagnostic evaluation of suspected lung cancer. This topic was the subject of a major update in the 2013 NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Non-Small Cell Lung Cancer. The NCCN Guidelines Insights focus on the major updates in the NCCN Guidelines and discuss the new updates in greater detail.

The predictive role of soluble programmed death ligand 1 in digestive system cancers.

Introduction: The prognostic role of soluble programmed death ligand 1 (sPD-L1) in digestive system cancers (DSCs) remains inconclusive. This study aimed to explore the predictive value of sPD-L1 expression in DSCs. Methods: Comprehensive searches were run on the electronic databases (PubMed, Web of Science, EMBASE, and the Cochrane Library) to identify studies that assessed the prognostic role of sPD-L1 in DSCs. Review Manager software (version 5.3) was used for all analyses. Pooled data for survival outcomes were measured as hazard ratios (HRs), 95% confidence intervals (CIs), and odds ratios and their 95% CIs. Results: The search identified 18 studies involving 2,070 patients with DSCs. The meta-outcome revealed that a high level of sPD-L1 was related to poorer overall survival (HR, 3.06; 95% CI: 2.22-4.22, p<0.001) and disease-free survival (HR, 2.53; 95% CI: 1.67-3.83, p<0.001) in DSCs. Individually, the prognostic significance of high level of sPD-L1 expression was the highest in hepatic cell carcinoma (HR, 4.76; p<0.001) followed by gastric cancer (HR=3.55, p<0.001). Conclusion: sPD-L1 may be a prognostic factor in DSCs for overall survival and disease-free survival. Inflammatory cytokines, treatment approaches, and other factors may affect the expression of sPD-L1. Therefore, the prognostic value of sPD-L1 for recurrence and metastasis should be further investigated. sPD-L1 may also predict response to treatment. Well-designed prospective studies with standard assessment methods should be conducted to determine the prognostic value of sPD-L1 in DSCs.

Respiratory Invariant Textures From Static Computed Tomography Scans for Explainable Lung Function Characterization.

PURPOSE: The inherent characteristics of lung tissue independent of breathing maneuvers may provide fundamental information for function assessment. This paper attempted to correlate textural signatures from computed tomography (CT) with pulmonary function measurements. MATERIALS AND METHODS: Twenty-one lung cancer patients with thoracic 4-dimensional CT, DTPA-single-photon emission CT ventilation ( VNM ) scans, and available spirometry measurements (forced expiratory volume in 1 s, FEV 1 ; forced vital capacity, FVC; and FEV 1 /FVC) were collected. In subregional feature discovery, function-correlated candidates were identified from 79 radiomic features based on the statistical strength to differentiate defected/nondefected lung regions. Feature maps (FMs) of selected candidates were generated on 4-dimensional CT phases for a voxel-wise feature distribution study. Quantitative metrics were applied for validations, including the Spearman correlation coefficient (SCC) and the Dice similarity coefficient for FM- VNM spatial agreement assessments, intraclass correlation coefficient for FM interphase robustness evaluations, and FM-spirometry comparisons. RESULTS: At the subregion level, 8 function-correlated features were identified (effect size>0.330). The FMs of candidates yielded moderate-to-strong voxel-wise correlations with the reference VNM . The FMs of gray level dependence matrix dependence nonuniformity showed the highest robust (intraclass correlation coefficient=0.96 and P <0.0001) spatial correlation, with median SCCs ranging from 0.54 to 0.59 throughout the 10 breathing phases. Its phase-averaged FM achieved a median SCC of 0.60, a median Dice similarity coefficient of 0.60 (0.65) for high (low) functional lung volumes, and a correlation of 0.565 (0.646) between the spatially averaged feature values and FEV 1 (FEV 1 /FVC). CONCLUSIONS: The results provide further insight into the underlying association of specific pulmonary textures with both local ( VNM ) and global (FEV 1 /FVC, FEV 1 ) functions. Further validations of the FM generalizability and the standardization of implementation protocols are warranted before clinically relevant investigations.

Dosimetric Effect of Thymus and Thoracic Duct on Radiation-Induced Lymphopenia in Patients With Primary Lung Cancer Who Received Thoracic Radiation.

Purpose: Radiation-induced lymphopenia is a well-recognized factor for tumor control and survival in patients with cancer. This study aimed to determine the role of radiation dose to the thymus and thoracic duct on radiation-induced lymphopenia. Methods and Materials: Patients with primary lung cancer treated with thoracic radiation therapy between May 2015 and February 2020 with whole blood count data were eligible. Clinical characteristics, including age, gender, histology, stage, chemotherapy regimen, radiation dosimetry, and absolute lymphocyte count (ALC) were collected. The thymus and thoracic duct were contoured by one investigator for consistency and checked by one senior physician. The primary endpoint was radiation-induced decrease in lymphocytes, defined as the difference in ALC (DALC) before and after radiation therapy. Results: The data of a total of 116 consecutive patients were retrospectively retrieved. Significant correlations were found between DALC and several clinical factors. These factors include stage, chemotherapy or concurrent chemoradiation, biologically effective dose (BED), mean lung dose, mean body dose, effective dose to immune cells (EDIC), mean thymus dose (MTD), and mean thoracic duct dose (MTDD) (all P < .05). Ridge regression showed that DALC = 0.0063 × BED + 0.0172 × EDIC + 0.0002 × MTD + 0.0147 × MTDD + 0.2510 (overall P = .00025 and F = 5.85). The combination model has the highest area under the curve of 0.77 (P < .001) when fitting the logistic regression model on DALC categorized as binary endpoint. The sensitivity and specificity of the combined model were 89% and 58%, respectively. Conclusions: This study demonstrated for the first time that radiation doses to the thymus and thoracic duct are strongly associated with radiation-induced lymphopenia patients with lung cancer. Further validation studies are needed to implement thymus and thoracic duct as organs at risk.

Artificial intelligence-assisted multistrategy image enhancement of chest X-rays for COVID-19 classification.

Background: The coronavirus disease 2019 (COVID-19) led to a dramatic increase in the number of cases of patients with pneumonia worldwide. In this study, we aimed to develop an AI-assisted multistrategy image enhancement technique for chest X-ray (CXR) images to improve the accuracy of COVID-19 classification. Methods: Our new classification strategy consisted of 3 parts. First, the improved U-Net model with a variational encoder segmented the lung region in the CXR images processed by histogram equalization. Second, the residual net (ResNet) model with multidilated-rate convolution layers was used to suppress the bone signals in the 217 lung-only CXR images. A total of 80% of the available data were allocated for training and validation. The other 20% of the remaining data were used for testing. The enhanced CXR images containing only soft tissue information were obtained. Third, the neural network model with a residual cascade was used for the super-resolution reconstruction of low-resolution bone-suppressed CXR images. The training and testing data consisted of 1,200 and 100 CXR images, respectively. To evaluate the new strategy, improved visual geometry group (VGG)-16 and ResNet-18 models were used for the COVID-19 classification task of 2,767 CXR images. The accuracy of the multistrategy enhanced CXR images was verified through comparative experiments with various enhancement images. In terms of quantitative verification, 8-fold cross-validation was performed on the bone suppression model. In terms of evaluating the COVID-19 classification, the CXR images obtained by the improved method were used to train 2 classification models. Results: Compared with other methods, the CXR images obtained based on the proposed model had better performance in the metrics of peak signal-to-noise ratio and root mean square error. The super-resolution CXR images of bone suppression obtained based on the neural network model were also anatomically close to the real CXR images. Compared with the initial CXR images, the classification accuracy rates of the internal and external testing data on the VGG-16 model increased by 5.09% and 12.81%, respectively, while the values increased by 3.51% and 18.20%, respectively, for the ResNet-18 model. The numerical results were better than those of the single-enhancement, double-enhancement, and no-enhancement CXR images. Conclusions: The multistrategy enhanced CXR images can help to classify COVID-19 more accurately than the other existing methods.

Sequential transarterial chemoembolisation and stereotactic body radiotherapy followed by immunotherapy as conversion therapy for patients with locally advanced, unresectable hepatocellular carcinoma (START-FIT): a single-arm, phase 2 trial.

BACKGROUND: The synergy between locoregional therapies and immune checkpoint inhibitors has not been investigated as conversion therapy for unresectable hepatocellular carcinoma. We aimed to investigate the activity of sequential transarterial chemoembolisation (TACE) and stereotactic body radiotherapy followed by avelumab (an anti-PD-L1 drug) for locally advanced, unresectable hepatocellular carcinoma. METHODS: START-FIT was a single-arm, phase 2 trial in patients with locally advanced hepatocellular carcinoma who were not suitable for curative treatment, conducted in two hospitals in Hong Kong and one in Shenzhen, China. Eligible patients were those aged 18 years or older with an Eastern Cooperative Oncology Group performance status 0-1, Child-Pugh liver function score A5 to B7, tumour size of at least 5 cm, a maximum of three tumour lesions, and adequate hepatic, renal, and bone marrow function. Participants received TACE on day 1, followed by stereotactic body radiotherapy (27·5-40·0 Gy in five fractions) at day 28. Avelumab (10 mg/kg) was administered 14 days following stereotactic body radiotherapy and every 2 weeks thereafter. The primary endpoint was the proportion of patients deemed amenable to curative treatment, defined as those who had a sustained complete or partial treatment response for at least 2 months and if curative treatment could be performed (ie, resection, radiofrequency ablation, or transplantation), analysed by intention to treat. Safety was also analysed in the intention-to-treat population. This trial is registered with ClinicalTrials.gov (NCT03817736) and has been completed. FINDINGS: Between March 18, 2019, and Jan 27, 2021, 33 patients (32 [97%] men and one [3%] woman) were enrolled. The median sum of the largest diameters of lesions was 15·1 cm (IQR 8·3-14·9). 21 (64%) patients had macrovascular invasion (hepatic vein [n=13], branched portal vein [n=3], or both [n=5]). Median follow-up was 17·2 months (IQR 7·8-25·8). 18 (55%) patients were deemed amenable to curative treatment: four (12%) of 33 patients had curative treatment (resection [n=2] or radiofrequency ablation [n=2]), and 14 (42%) had a radiological complete response and opted for close surveillance. 11 (33%) of 33 patients had treatment-related adverse events that were grade 3 or worse. The most common treatment-related grade 3 or worse adverse event was transient increase in alanine aminotransferase or aspartate aminotransferase (five [15%]) after TACE. Five (15%) patients developed immune-related adverse events of grade 3 or worse (three had hepatitis, two had dermatitis). INTERPRETATION: To our knowledge, this is the first prospective trial using the combination of immunotherapy and locoregional treatment as conversion therapy for locally advanced unresectable hepatocellular carcinoma, with promising results. Future randomised trials with larger cohorts of patients are warranted. FUNDING: Merck.

Deep learning attention-guided radiomics for COVID-19 chest radiograph classification.

Background: Accurate assessment of coronavirus disease 2019 (COVID-19) lung involvement through chest radiograph plays an important role in effective management of the infection. This study aims to develop a two-step feature merging method to integrate image features from deep learning and radiomics to differentiate COVID-19, non-COVID-19 pneumonia and normal chest radiographs (CXR). Methods: In this study, a deformable convolutional neural network (deformable CNN) was developed and used as a feature extractor to obtain 1,024-dimensional deep learning latent representation (DLR) features. Then 1,069-dimensional radiomics features were extracted from the region of interest (ROI) guided by deformable CNN's attention. The two feature sets were concatenated to generate a merged feature set for classification. For comparative experiments, the same process has been applied to the DLR-only feature set for verifying the effectiveness of feature concatenation. Results: Using the merged feature set resulted in an overall average accuracy of 91.0% for three-class classification, representing a statistically significant improvement of 0.6% compared to the DLR-only classification. The recall and precision of classification into the COVID-19 class were 0.926 and 0.976, respectively. The feature merging method was shown to significantly improve the classification performance as compared to using only deep learning features, regardless of choice of classifier (P value <0.0001). Three classes' F1-score were 0.892, 0.890, and 0.950 correspondingly (i.e., normal, non-COVID-19 pneumonia, COVID-19). Conclusions: A two-step COVID-19 classification framework integrating information from both DLR and radiomics features (guided by deep learning attention mechanism) has been developed. The proposed feature merging method has been shown to improve the performance of chest radiograph classification as compared to the case of using only deep learning features.

Efficacy, safety, and correlative biomarkers of bintrafusp alfa in recurrent or metastatic nasopharyngeal cancer patients: a phase II clinical trial.

Background: The strategy of dual blockade of TGF-ß and PD-L1 pathways has not been previously tested in platinum-refractory recurrent or metastatic nasopharyngeal cancer (R/M NPC) patients. This study aimed to evaluate the safety and efficacy of bintrafusp alfa in refractory R/M NPC patients. Methods: In this single-arm, single-centre phase II clinical trial, 38 histologically confirmed R/M NPC patients were enrolled and administered with bintrafusp alfa every 2 weeks. Primary endpoint was objective response rate (ORR) per Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1). Secondary endpoints included progression-free survival (PFS), overall survival (OS), duration of response (DOR), and safety. Findings: Thirty-eight patients were accrued (33 men; median age, 54 years). ORR was 23.7% (complete response, n = 2; partial response, n = 7). The median DOR was 19.2 months, median PFS was 2.3 months, median OS was 17.0 months, and 1-year OS rate was 63.2%. Unfortunately, 25 patients (65.7%) progressed within 8 weeks of treatment, 15 patients (39.5%) and 8 patients (21.1%) developed hyper-progressive disease (HPD) per RECIST v1.1 and tumor growth rate (TGR) ratio respectively. Sixteen patients (42.4%) experienced ≥ grade 3 treatment-related adverse events (TRAEs), most commonly anemia (n = 9, 23.7%) and secondary malignancies (n = 4, 10.5%). TRAEs led to permanent treatment discontinuation in 7 patients. Patients with strong suppression of plasma TGFß1 level at week 8 were unexpectedly associated with worse ORR (9.1% vs 44.4%, P = 0.046) and development of HPD. There was no correlation between PD-L1 expression and ORR. Interpretation: Bintrafusp alfa demonstrated modest activity in R/M NPC but high rates of HPD and treatment discontinuation secondary to TRAEs are concerning. Funding: The project was supported by Alice Ho Miu Ling Nethersole Charity Foundation Professorship Endowed Fund and Merck KGaA.

The management of patients with stage IIIA non-small cell lung cancer with N2 mediastinal node involvement.

Patients with stage IIIA non-small cell lung cancer, determined based on involvement of ipsilateral mediastinal lymph nodes, represent the most challenging management problem in this disease. Patients with this stage disease may have very different degrees of lymph node involvement. The pathologic confirmation of this involvement is a key step in the therapeutic decision. The difference in the degree of lymph node compromise has prognostic and treatment implications. Based on multiple considerations, patients can be treated with induction chemotherapy, chemoradiotherapy followed by surgery, or definitive chemoradiotherapy without surgery. Data derived from clinical trials have provided incomplete guidance for physicians and their patients. The best therapeutic plan is achieved through the multidisciplinary cooperation of a team specialized in lung cancer.

Potential Determinants for Radiation-Induced Lymphopenia in Patients With Breast Cancer Using Interpretable Machine Learning Approach.

Radiation-induced lymphopenia is known for its survival significance in patients with breast cancer treated with radiation therapy. This study aimed to evaluate the impact of radiotherapy on lymphocytes by applying machine learning strategies. We used Extreme Gradient Boosting (XGboost) to predict the event of lymphopenia (grade≥1) and conduced an independent validation. Then, we induced feature attribution analysis (Shapley additive explanation, SHAP) in explaining the XGboost models to explore the directional contribution of each feature to lymphopenia. Finally, we implemented the proof-of-concept clinical validation. The results showed that the XGboost models had rigorous generalization performances (accuracies 0.764 and ROC-AUC 0.841, respectively) in the independent cohort. The baseline lymphocyte counts are the most protective feature (SHAP = 5.226, direction of SHAP = -0.964). Baseline platelets and monocytes also played important protective roles. The usage of taxane only chemotherapy was less risk on lymphopenia than the combination of anthracycline and taxane. By the contribution analysis of dose, we identified that firstly lymphocytes were sensitive to a radiation dose less than 4Gy; secondly the irradiation volume was more important in promoting lymphopenia than the irradiation dose; thirdly the irradiation dose promoted the event of lymphopenia when the irradiation volume was fixed. Overall, our findings paved the way to clarifying the radiation dose volume effect. To avoid radiation-induced lymphopenia, irradiation volume should be kept to a minimum during the planning process, as long as the target coverage is not compromised.

Immune related biomarkers for cancer metastasis to the brain.

Brain metastasis accounts for a large number of cancer-related deaths. The host immune system, involved at each step of the metastatic cascade, plays an important role in both the initiation of the brain metastasis and their treatment responses to various modalities, through either local and or systemic effect. However, few reliable immune biomarkers have been identified in predicting the development and the treatment outcome in patients with cancer brain metastasis. Here, we provide a focused perspective of immune related biomarkers for cancer metastasis to the brain and a thorough discussion of the potential utilization of specific biomarkers such as tumor mutation burden (TMB), genetic markers, circulating and tumor-infiltrating immune cells, cytokines, in predicting the brain disease progression and regression after therapeutic intervention. We hope to inspire the field to extend the research and establish practical guidelines for developing and validating immune related biomarkers to provide personalized treatment and improve treatment outcomes in patients with metastatic brain cancers.