Targeted natural killer cell–based adoptive immunotherapy for the treatment of patients with NSCLC after radiochemotherapy: a randomized phase II clinical trial

Purpose: Non–small cell lung cancer (NSCLC) is a fatal disease with poor prognosis. A membrane-bound form of Hsp70 (mHsp70) which is selectively expressed on high-risk tumors serves as a target for mHsp70-targeting natural killer (NK) cells. Patients with advanced mHsp70-positive NSCLC may therefore benefit from a therapeutic intervention involving mHsp70-targeting NK cells. The randomized phase II clinical trial (EudraCT2008-002130-30) explores tolerability and efficacy of ex vivo–activated NK cells in patients with NSCLC after radiochemotherapy (RCT). Patients and Methods: Patients with unresectable, mHsp70-positive NSCLC (stage IIIa/b) received 4 cycles of autologous NK cells activated ex vivo with TKD/IL2 [interventional arm (INT)] after RCT (60–70 Gy, platinum-based chemotherapy) or RCT alone [control arm (CTRL)]. The primary objective was progression-free survival (PFS), and secondary objectives were the assessment of quality of life (QoL, QLQ-LC13), toxicity, and immunobiological responses. Results: The NK-cell therapy after RCT was well tolerated, and no differences in QoL parameters between the two study arms were detected. Estimated 1-year probabilities for PFS were 67% [95% confidence interval (CI), 19%–90%] for the INT arm and 33% (95% CI, 5%–68%) for the CTRL arm (P = 0.36, 1-sided log-rank test). Clinical responses in the INT group were associated with an increase in the prevalence of activated NK cells in their peripheral blood

R0 resection following chemo (radio)therapy improves survival of primary inoperable pancreatic cancer patients. Interim results of the German randomized CONKO-007± trial

Abstract Purpose Chemotherapy with or without radiotherapy is the standard in patients with initially nonmetastatic unresectable pancreatic cancer. Additional surgery is in discussion. The CONKO-007 multicenter randomized trial examines the value of radiotherapy. Our interim analysis showed a significant effect of surgery, which may be relevant to clinical practice. Methods One hundred eighty patients received induction chemotherapy (gemcitabine or FOLFIRINOX). Patients without tumor progression were randomized to either chemotherapy alone or to concurrent chemoradiotherapy. At the end of therapy, a panel of five independent pancreatic surgeons judged the resectability of the tumor. Results Following induction chemotherapy, 126/180 patients (70.0%) were randomized to further treatment. Following study treatment, 36/126 patients (28.5%) underwent surgery; (R0: 25/126 [19.8%]; R1/R2/Rx [n = 11/126; 6.1%]). Disease-free survival (DFS) and overall survival (OS) were significantly better for patients with R0 resected tumors (median DFS and OS: 16.6 months and 26.5 months, respectively) than for nonoperated patients (median DFS and OS: 11.9 months and 16.5 months, respectively; p = 0.003). In the 25 patients with R0 resected tumors before treatment, only 6/113 (5.3%) of the recommendations of the panel surgeons recommended R0 resectability, compared with 17/48 (35.4%) after treatment (p < 0.001). Conclusion Tumor resectability of pancreatic cancer staged as unresectable at primary diagnosis should be reassessed after neoadjuvant treatment. The patient should undergo surgery if a resectability is reached, as this significantly improves their prognosis

Evaluating predictive modeling algorithms to assess patient eligibility for clinical trials from routine data

Background The necessity to translate eligibility criteria from free text into decision rules that are compatible with data from the electronic health record (EHR) constitutes the main challenge when developing and deploying clinical trial recruitment support systems. Recruitment decisions based on case-based reasoning, i.e. using past cases rather than explicit rules, could dispense with the need for translating eligibility criteria and could also be implemented largely independently from the terminology of the EHR’s database. We evaluated the feasibility of predictive modeling to assess the eligibility of patients for clinical trials and report on a prototype’s performance for different system configurations. Methods The prototype worked by using existing basic patient data of manually assessed eligible and ineligible patients to induce prediction models. Performance was measured retrospectively for three clinical trials by plotting receiver operating characteristic curves and comparing the area under the curve (ROC-AUC) for different prediction algorithms, different sizes of the learning set and different numbers and aggregation levels of the patient attributes. Results Random forests were generally among the best performing models with a maximum ROC-AUC of 0.81 (CI: 0.72-0.88) for trial A, 0.96 (CI: 0.95-0.97) for trial B and 0.99 (CI: 0.98-0.99) for trial C. The full potential of this algorithm was reached after learning from approximately 200 manually screened patients (eligible and ineligible). Neither block- nor category-level aggregation of diagnosis and procedure codes influenced the algorithms’ performance substantially. Conclusions Our results indicate that predictive modeling is a feasible approach to support patient recruitment into clinical trials. Its major advantages over the commonly applied rule-based systems are its independency from the concrete representation of eligibility criteria and EHR data and its potential for automation

12 × 6 Gy stereotactic radiotherapy for lung tumors. Is there a difference in response between lung metastases and primary bronchial carcinoma?

Purpose!#!The aim of this study was to evaluate the safety and long-term tumor control after stereotactic radiotherapy (SRT) with 12 × 6 Gy of patients with primary bronchial carcinoma (BC) or with pulmonary metastases (MET) of various solid tumors. Local progression-free survival (LPFS), progression-free survival (PFS), overall survival (OS), and prognostic factors were compared.!##!Methods!#!Between May 2012 and January 2020, 168 patients with 206 pulmonary lesions (170 MET and 36 primary BC) were treated with 12 × 6 Gy (BED!##!Results!#!The median follow-up was 16.26 months (range: 0.46-89.34) for BC and 19.18 months (0.89-91.11) for MET. Survival rates at 3 years were: OS 43% for BC and 35% for MET; LPFS BC 96% and MET 85%; PFS BC 35% and MET 29%. The most frequently observed grade 3 adverse events (AEs) were pneumonitis (5.9% BC, 4.8% MET), pulmonary fibrosis (2.9% BC, 4% MET), and pulmonary embolism (2.9% BC, 0.8% MET). The favorable prognostic effects on overall survival of patients with MET were female gender (log-rank: p &amp;lt; 0.001), no systemic progression (log-rank; p = 0.048, multivariate COX regression p = 0.039), and malignant melanoma histology (log-rank; p = 0.015, multivariate COX regression p = 0.020). For patients with BC, it was tumor location within the lower lobe (vs. upper lobe, log-rank p = 0.027). LPFS of patients with metastatic disease was beneficially influenced by female gender (log-rank: p = 0.049).!##!Conclusion!#!The treatment concept of 12 × 6 Gy is associated with 96% local progression-free survival for BC and 85% for pulmonary metastases after 3 years. There was no difference in response after SRT of primary lung carcinoma or pulmonary metastases

Electronic Support for Retrospective Analysis in the Field of Radiation Oncology: Proof of Principle Using an Example of Fractionated Stereotactic Radiotherapy of 251 Meningioma Patients

Introduction: The purpose of this study is to verify the possible benefit of a clinical data warehouse (DWH) for retrospective analysis in the field of radiation oncology. Material and methods: We manually and electronically (using DWH) evaluated demographic, radiotherapy, and outcome data from 251 meningioma patients, who were irradiated from January 2002 to January 2015 at the Department of Radiation Oncology of the Erlangen University Hospital. Furthermore, we linked the Oncology Information System (OIS) MOSAIQ® to the DWH in order to gain access to irradiation data. We compared the manual and electronic data retrieval method in terms of congruence of data, corresponding time, and personal requirements (physician, physicist, scientific associate). Results: The electronically supported data retrieval (DWH) showed an average of 93.9% correct data and significantly (p = 0.009) better result compared to manual data retrieval (91.2%). Utilizing a DWH enables the user to replace large amounts of manual activities (668 h), offers the ability to significantly reduce data collection time and labor demand (35 h), while simultaneously improving data quality. In our case, work time for manually data retrieval was 637 h for the scientific assistant, 26 h for the medical physicist, and 5 h for the physician (total 668 h). Conclusion: Our study shows that a DWH is particularly useful for retrospective analysis in the radiation oncology field. Routine clinical data for a large patient group can be provided ready for analysis to the scientist and data collection time can be significantly reduced. Furthermore, linking multiple data sources in a DWH offers the ability to improve data quality for retrospective analysis, and future research can be simplified

Newly Synthesized Melphalan Analogs Induce DNA Damage and Mitotic Catastrophe in Hematological Malignant Cancer Cells

Myeloablative therapy with highdoses of the cytostatic drug melphalan (MEL) in preparation for hematopoietic cell transplantation is the standard of care for multiple myeloma (MM) patients. Melphalan is a bifunctional alkylating agent that covalently binds to nucleophilic sites in the DNA and effective in the treatment, but unfortunately has limited therapeutic benefit. Therefore, new approaches are urgently needed for patients who are resistant to existing standard treatment with MEL. Regulating the pharmacological activity of drug molecules by modifying their structure is one method for improving their effectiveness. The purpose of this work was to analyze the physicochemical and biological properties of newly synthesized melphalan derivatives (EE-MEL, EM-MEL, EM-MOR-MEL, EM-I-MEL, EM-T-MEL) obtained through the esterification of the carboxyl group and the replacement of the the amino group with an amidine group. Compounds were selected based on our previous studies for their improved anticancer properties in comparison with the original drug. For this, we first evaluated the physicochemical properties using the circular dichroism technique, then analyzed the zeta potential and the hydrodynamic diameters of the particles. Then, the in vitro biological properties of the analogs were tested on multiple myeloma (RPMI8226), acute monocytic leukemia (THP1), and promyelocytic leukemia (HL60) cells as model systems for hematological malignant cells. DNA damage was assessed by immunostaining &gamma;H2AX, cell cycle distribution changes by propidium iodide (PI) staining, and cell death by the activation of caspase 2. We proved that the newly synthesized derivatives, in particular EM-MOR-MEL and EM-T-MEL, affected the B-DNA conformation, thus increasing the DNA damage. As a result of the DNA changes, the cell cycle was arrested in the S and G2/M phases. The cell death occurred by activating a mitotic catastrophe. Our investigations suggest that the analogs EM-MOR-MEL and EM-T-MEL have better anti-cancer activity in multiple myeloma cells than the currently used melphalan

Long-term control with chemoradiation of initially metastatic mixed adenoneuroendocrine carcinoma of the rectum: a case report

Abstract Background Mixed adenoneuroendocrine carcinomas are highly malignant tumors with both adenocarcinomatous and neuroendocrine components. They can originate in any organ but are more common in the rectum. Due to their rarity, current treatment recommendations for mixed adenoneuroendocrine carcinoma are based on limited data and follow general guidelines for the management of adenocarcinomas and neuroendocrine neoplasms. Uncertainty regarding the efficacy of the available local and systemic treatment strategies is a compounding issue. Even those patients with locally limited disease have a relatively short life expectancy. In this report, we describe a case of deep rectal mixed adenoneuroendocrine carcinoma with long survival after chemoradiation. Case presentation A 48-year-old Caucasian woman was diagnosed with a grade 3 rectal adenocarcinoma combined with a poorly differentiated large cell neuroendocrine carcinoma component and synchronous metastases (cT3cN1cM1) in both lobes of the liver in 2012. She received concomitant chemoradiotherapy followed by four additional cycles of cisplatin plus irinotecan. Initial treatment induced complete remission of the rectal tumor and liver metastases. Consequently, it was not necessary to surgically resect the primary tumor or any of the metastases. Three months after the end of treatment, one metastasis in the first segment of the liver showed regrowth, and stereotactic body radiotherapy of the metastasis and chemotherapy resulted in a clinical complete response. The patient has been recurrence-free for more than 5 years. Conclusions Extended long-term control of a poorly differentiated metastatic (stage IV) mixed adenoneuroendocrine carcinoma is rare. The multimodal first- and second-line regimens of radiotherapy and chemotherapy described in this case report represent a new therapeutic approach. Encouraged by the results in this case, we compiled a review of the literature on mixed adenoneuroendocrine carcinoma

Long-term control with chemoradiation of initially metastatic mixed adenoneuroendocrine carcinoma of the rectum: a case report

Abstract Background Mixed adenoneuroendocrine carcinomas are highly malignant tumors with both adenocarcinomatous and neuroendocrine components. They can originate in any organ but are more common in the rectum. Due to their rarity, current treatment recommendations for mixed adenoneuroendocrine carcinoma are based on limited data and follow general guidelines for the management of adenocarcinomas and neuroendocrine neoplasms. Uncertainty regarding the efficacy of the available local and systemic treatment strategies is a compounding issue. Even those patients with locally limited disease have a relatively short life expectancy. In this report, we describe a case of deep rectal mixed adenoneuroendocrine carcinoma with long survival after chemoradiation. Case presentation A 48-year-old Caucasian woman was diagnosed with a grade 3 rectal adenocarcinoma combined with a poorly differentiated large cell neuroendocrine carcinoma component and synchronous metastases (cT3cN1cM1) in both lobes of the liver in 2012. She received concomitant chemoradiotherapy followed by four additional cycles of cisplatin plus irinotecan. Initial treatment induced complete remission of the rectal tumor and liver metastases. Consequently, it was not necessary to surgically resect the primary tumor or any of the metastases. Three months after the end of treatment, one metastasis in the first segment of the liver showed regrowth, and stereotactic body radiotherapy of the metastasis and chemotherapy resulted in a clinical complete response. The patient has been recurrence-free for more than 5 years. Conclusions Extended long-term control of a poorly differentiated metastatic (stage IV) mixed adenoneuroendocrine carcinoma is rare. The multimodal first- and second-line regimens of radiotherapy and chemotherapy described in this case report represent a new therapeutic approach. Encouraged by the results in this case, we compiled a review of the literature on mixed adenoneuroendocrine carcinoma

Evaluating predictive modeling algorithms to assess patient eligibility for clinical trials from routine data

Background The necessity to translate eligibility criteria from free text into decision rules that are compatible with data from the electronic health record (EHR) constitutes the main challenge when developing and deploying clinical trial recruitment support systems. Recruitment decisions based on case-based reasoning, i.e. using past cases rather than explicit rules, could dispense with the need for translating eligibility criteria and could also be implemented largely independently from the terminology of the EHR’s database. We evaluated the feasibility of predictive modeling to assess the eligibility of patients for clinical trials and report on a prototype’s performance for different system configurations. Methods The prototype worked by using existing basic patient data of manually assessed eligible and ineligible patients to induce prediction models. Performance was measured retrospectively for three clinical trials by plotting receiver operating characteristic curves and comparing the area under the curve (ROC-AUC) for different prediction algorithms, different sizes of the learning set and different numbers and aggregation levels of the patient attributes. Results Random forests were generally among the best performing models with a maximum ROC-AUC of 0.81 (CI: 0.72-0.88) for trial A, 0.96 (CI: 0.95-0.97) for trial B and 0.99 (CI: 0.98-0.99) for trial C. The full potential of this algorithm was reached after learning from approximately 200 manually screened patients (eligible and ineligible). Neither block- nor category-level aggregation of diagnosis and procedure codes influenced the algorithms’ performance substantially. Conclusions Our results indicate that predictive modeling is a feasible approach to support patient recruitment into clinical trials. Its major advantages over the commonly applied rule-based systems are its independency from the concrete representation of eligibility criteria and EHR data and its potential for automation