Pembrolizumab combined with stereotactic body radiotherapy in a patient with human immunodeficiency virus and advanced non-small cell lung cancer: a case report

Abstract Background Pembrolizumab has significantly improved outcomes in patients with advanced non-small cell lung cancer. Combining programmed death-1 inhibitor with stereotactic body radiotherapy showed a slight toxicity and good benefits in recent clinical trials. However, patients infected with human immunodeficiency virus were excluded from most trials because it was assumed that their anti-tumor immunity was compromised compared with immunocompetent patients. Case presentation In June 2016, a 52-year-old Chinese man presented with human immunodeficiency virus and lung adenocarcinoma (T1bN3M1b). From November 2016 to December 2016, systemic chemotherapy and palliative radiotherapy for bone metastasis of femoral neck were carried out, but the tumor progressed. In January 2017, after immunochemistry detection of programmed death-1 and programmed death-ligand 1 expression (both > 50%), pembrolizumab was started. Three weeks after pembrolizumab, we combined stereotactic body radiotherapy for the primary lung tumor. He received no comfort and his CD4 lymphocyte count was stable. Human immunodeficiency virus-ribonucleic acid remained below the limits of detection. In March 2017, after three cycles of pembrolizumab and 5 weeks of stereotactic body radiotherapy therapy, he suddenly presented with palpitations. Emergency computed tomography scanning showed massive pericardial effusion and interstitial pneumonia. So we interrupted the pembrolizumab use and initiated treatment with prednisolone 1 mg/kg; however, the tumor progressed. Then, his CD4 lymphocyte count declined. Finally he died in June 2017 due to dyscrasia. Conclusions Pembrolizumab combined with SBRT therapy for patients with human immunodeficiency virus infection and non-small cell lung cancer may lead to serious immune-related adverse events and more clinical trials are needed

The Application and Development of Deep Learning in Radiotherapy: A Systematic Review

With the massive use of computers, the growth and explosion of data has greatly promoted the development of artificial intelligence (AI). The rise of deep learning (DL) algorithms, such as convolutional neural networks (CNN), has provided radiation oncologists with many promising tools that can simplify the complex radiotherapy process in the clinical work of radiation oncology, improve the accuracy and objectivity of diagnosis, and reduce the workload, thus enabling clinicians to spend more time on advanced decision-making tasks. As the development of DL gets closer to clinical practice, radiation oncologists will need to be more familiar with its principles to properly evaluate and use this powerful tool. In this paper, we explain the development and basic concepts of AI and discuss its application in radiation oncology based on different task categories of DL algorithms. This work clarifies the possibility of further development of DL in radiation oncology

Immunotherapy in head and neck cancer: Harnessing profit on a system disruption

International audienceImmune system deregulation and evasion play a key role in cancers’ evolution and progression, including squamous cell carcinoma of the head and neck (SCCHN). Development of basic research proposed a whole new vision of cancer treatment, based on a strong biological rational, and targeting intrinsic deregulations. Immunotherapies provide an encouraging strategy for patients’ improved outcomes. Immune-based therapies could act on cancer growth and/or development throughout many pathways. If cetuximab is for now the only monoclonal antibody approved for SCCHN management, other strategies, e.g. immune checkpoints openers, are arousing enthusiasm. Clinical trials are multiplying in patients with recurrent/metastatic SCCHN and primary results offer promising outcomes. Prospects of combining various immunotherapies with more established treatments, such as chemotherapy and radiotherapy, seem very encouraging and could provide synergistic benefits. Ongoing phase III clinical trials should soon enlighten us on the next “standard of care” for SCCHN. In the present review we summarized the different immunotherapy strategies that are currently under clinical investigation for SCCHN’ medical care

Targeting stem cells by radiation: From the biological angle to clinical aspects

International audienceRadiotherapy is a cornerstone of anticancer treatment. However in spite of technical evolutions, important rates of failure and of toxicity are still reported. Although numerous pre-clinical data have been published, we address the subject of radiotherapy-stem cells interaction from the clinical efficacy and toxicity perspective. On one side, cancer stem cells (CSCs) have been recently evidenced in most of solid tumor primary locations and are thought to drive radio-resistance phenomena. It is particularly suggested in glioblastoma, where CSCs were showed to be housed in the subventricular zone (SVZ). In recent retrospective studies, the radiation dose to SVZ was identified as an independent factor significantly influencing overall survival. On the other side, healthy tissue stem cells radio-destruction has been recently suggested to cause two of the most quality of life-impacting side effects of radiotherapy, namely memory disorders after brain radiotherapy, and xerostomia after head and neck radiotherapy. Recent publications studying the impact of a radiation dose decrease on healthy brain and salivary stem cells niches suggested significantly reduced long term toxicities. Stem cells comprehension should be a high priority for radiation oncologists, as this particular cell population seems able to widely modulate the efficacy/toxicity ratio of radiotherapy in real life patients

Combined Radiomics–Clinical Model to Predict Radiotherapy Response in Inoperable Stage III and IV Non-Small-Cell Lung Cancer

Purpose: Radiotherapy is a promising treatment option for lung cancer, but patients’ responses vary. The purpose of the study was to investigate the potential of radiomics and clinical signature for predicting the radiotherapy sensitivity and overall survival of inoperable stage III and IV non-small-cell lung cancer (NSCLC) patients. Materials: This retrospective study collected 104 inoperable stage III and IV NSCLC patients at the Yunnan Cancer Hospital from October 2016 to September 2020. They were divided into radiation-sensitive and non-sensitive groups. We used analysis of variance (ANOVA) to select features and support vector machine (SVM) to build the radiomic model. Furthermore, the logistic regression method was used to screen out clinically relevant predictive factors and construct the combined model of radiomics–clinical features. Finally, survival was estimated using the Kaplan–Meier method. Results: There were 40 patients in the radiation-sensitive group and 64 in the non-sensitive group. These patients were divided into training set (73 cases) and testing set (31 cases) according to the ratio of 7:3. Nine radiomics features and one clinical feature were significantly associated with radiotherapy sensitivity. Both the radiomics model and combined model have good predictive performance (the areas under the curve (AUC) values of the testing set were 0.864 (95% confidence interval [CI]: 0.683-0.996) and 0.868 (95% CI: 0.689-1.000), respectively). Only platelet level status was associated with overall survival. Conclusion: The combined model constructed based on radiomics and clinical features can effectively identify the radiation-sensitive population and provide valuable clinical information. Patients with higher platelet levels may have a poor prognosis