Long-term survival follow-up for tebentafusp in previously treated metastatic uveal melanoma.

BACKGROUND: Tebentafusp, a bispecific (gp100×CD3) ImmTAC, significantly improved overall survival (OS) outcomes for HLA-A*02:01+ adult patients with untreated metastatic uveal melanoma (mUM) and showed promising survival in previously treated mUM with 1-year OS of 62% in the primary analysis of study IMCgp100-102. Here we report long-term outcomes from this phase 1/2 study in pretreated mUM. PATIENTS AND METHODS: Patients with previously treated mUM received tebentafusp weekly intravenous at 20 µg dose 1, 30 µg dose 2 and either 54, 64, 68, or 73 µg (phase 1) or 68 µg (phase 2) dose 3+. The primary objective was overall response rate. Secondary objectives included OS and safety. OS was estimated by Kaplan-Meier methods. Association between OS and baseline covariates, on-treatment Response Evaluation Criteria in Solid Tumors (RECIST) response, baseline tumor biopsy and circulating-tumor DNA (ctDNA) changes were assessed. RESULTS: 146 patients were treated with tebentafusp: 19 in phase 1 and 127 in phase 2. With a median follow-up duration of 48.5 months, the median OS was 17.4 months (95% CI, 13.1 to 22.8), and the 1-year, 2-year, 3-year and 4-year OS rates were 62%, 40%, 23% and 14%, respectively. Improved survival was associated with lower ctDNA baseline levels and greater ctDNA reductions by week 9 on-treatment, with 100% 1-year, 73% 2-year and 45% 3-year OS rates for patients with ctDNA clearance. Baseline gp100 expression was not associated with survival, despite more RECIST responses among patients with higher expression. No new safety signals were reported with long-term dosing. CONCLUSIONS: This study represents the longest follow-up of a Tcell receptor bispecific to date and confirms the durable survival benefits achieved with tebentafusp in previously treated mUM with good tolerability long-term. A role for ctDNA reduction as an early indicator of clinical benefit was again suggested for patients treated with tebentafusp.

Clinical and molecular response to tebentafusp in previously treated patients with metastatic uveal melanoma: a phase 2 trial.

In patients with previously treated metastatic uveal melanoma, the historical 1 year overall survival rate is 37% with a median overall survival of 7.8 months. We conducted a multicenter, single-arm, open-label phase 2 study of tebentafusp, a soluble T cell receptor bispecific (gp100×CD3), in 127 patients with treatment-refractory metastatic uveal melanoma (NCT02570308). The primary endpoint was the estimation of objective response rate based on RECIST (Response Evaluation Criteria in Solid Tumours) v1.1. Secondary objectives included safety, overall survival, progression-free survival and disease control rate. All patients had at least one treatment-related adverse event, with rash (87%), pyrexia (80%) and pruritus (67%) being the most common. Toxicity was mostly mild to moderate in severity but was greatly reduced in incidence and intensity after the initial three doses. Despite a low overall response rate of 5% (95% CI: 2-10%), the 1 year overall survival rate was 62% (95% CI: 53-70%) with a median overall survival of 16.8 months (95% CI: 12.9-21.3), suggesting benefit beyond traditional radiographic-based response criteria. In an exploratory analysis, early on-treatment reduction in circulating tumour DNA was strongly associated with overall survival, even in patients with radiographic progression. Our findings indicate that tebentafusp has promising clinical activity with an acceptable safety profile in patients with previously treated metastatic uveal melanoma, and data suggesting ctDNA as an early indicator of clinical benefit from tebentafusp need confirmation in a randomized trial.

Implementing Real-World RECIST-based Tumor Response Assessment in Patients With Metastatic Non-small Cell Lung Cancer.

BACKGROUND: To accelerate drug approvals while maintaining scientific rigor in the evaluation of a therapeutic's efficacy and safety, the United States Food and Drug Administration now considers real-world data (RWD) to support New Drug Applications and expanded indications. Response Evaluation Criteria in Solid Tumors (RECIST) are the gold standard in clinical trials, but the derivation of RECIST-based treatment response from RWD is unproven. This study investigated the feasibility of implementing RECIST criteria in RWD by comparing lung cancer response assessments from RECIST-based measurement of lesions on archived radiologic films with results from medical oncologist and radiologist narratives recorded in electronic health records (EHR). MATERIALS AND METHODS: Response to index treatment via different assessment approaches was compared among 30 metastatic non-small cell lung cancer (mNSCLC) patients receiving systemic treatment (index) after progression on a platinum or anti-PD(L)-1-containing regimen. Specifically, responses based on assessments documented in the medical oncologists' narratives were compared to a radiologist's assessments of archived images using RECIST v1.1 criteria. Each patient's best overall response was characterized as complete or partial (CR/PR), stable disease (SD), progressive disease (PD), or not evaluable (NE). RESULTS: Similar distributions of best overall response and substantial concordance (77%) between medical oncologist-reported and radiologist re-assessed responses were observed. There were no instances of CR/PR to PD or PD to CR/PR discordance. CONCLUSIONS: Results suggest that accurate treatment responses, similar to RECIST, may be derived using RWD. Further validation and improvement of real-world response assessment are needed to develop a scalable real-world approach for response assessment.

Customizable Natural Language Processing Biomarker Extraction Tool.

PURPOSE: Natural language processing (NLP) in pathology reports to extract biomarker information is an ongoing area of research. MetaMap is a natural language processing tool developed and funded by the National Library of Medicine to map biomedical text to the Unified Medical Language System Metathesaurus by applying specific tags to clinically relevant terms. Although results are useful without additional postprocessing, these tags lack important contextual information. METHODS: Our novel method takes terminology-driven semantic tags and incorporates those into a semantic frame that is task-specific to add necessary context to MetaMap. We use important contextual information to capture biomarker results to support Community Health System's use of Precision Medicine treatments for patients with cancer. For each biomarker, the name, type, numeric quantifiers, non-numeric qualifiers, and the time frame are extracted. These fields then associate biomarkers with their context in the pathology report such as test type, probe intensity, copy-number changes, and even failed results. A selection of 6,713 relevant reports contained the following standard-of-care biomarkers for metastatic breast cancer: breast cancer gene 1 and 2, estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and programmed death-ligand 1. RESULTS: The method was tested on pathology reports from the internal pathology laboratory at Henry Ford Health System. A certified tumor registrar reviewed 400 tests, which showed > 95% accuracy for all extracted biomarker types. CONCLUSION: Using this new method, it is possible to extract high-quality, contextual biomarker information, and this represents a significant advance in biomarker extraction.

Integrated Biomarkers for the Management of Indeterminate Pulmonary Nodules.

Rationale: Patients with indeterminate pulmonary nodules (IPNs) at risk of cancer undergo high rates of invasive, costly, and morbid procedures. Objectives: To train and externally validate a risk prediction model that combined clinical, blood, and imaging biomarkers to improve the noninvasive management of IPNs. Methods: In this prospectively collected, retrospective blinded evaluation study, probability of cancer was calculated for 456 patient nodules using the Mayo Clinic model, and patients were categorized into low-, intermediate-, and high-risk groups. A combined biomarker model (CBM) including clinical variables, serum high sensitivity CYFRA 21-1 level, and a radiomic signature was trained in cohort 1 (n = 170) and validated in cohorts 2-4 (total n = 286). All patients were pooled to recalibrate the model for clinical implementation. The clinical utility of the CBM compared with current clinical care was evaluated in 2 cohorts. Measurements and Main Results: The CBM provided improved diagnostic accuracy over the Mayo Clinic model with an improvement in area under the curve of 0.124 (95% bootstrap confidence interval, 0.091-0.156; P < 2 × 10-16). Applying 10% and 70% risk thresholds resulted in a bias-corrected clinical reclassification index for cases and control subjects of 0.15 and 0.12, respectively. A clinical utility analysis of patient medical records estimated that a CBM-guided strategy would have reduced invasive procedures from 62.9% to 50.6% in the intermediate-risk benign population and shortened the median time to diagnosis of cancer from 60 to 21 days in intermediate-risk cancers. Conclusions: Integration of clinical, blood, and image biomarkers improves noninvasive diagnosis of patients with IPNs, potentially reducing the rate of unnecessary invasive procedures while shortening the time to diagnosis.

Validation of a Mortality Composite Score in the Real-World Setting: Overcoming Source-Specific Disparities and Biases.

PURPOSE: This study tested whether a composite mortality score could overcome gaps and potential biases in individual real-world mortality data sources. Complete and accurate mortality data are necessary to calculate important outcomes in oncology, including overall survival. However, in the United States, there is not a single complete and broadly applicable mortality data source. It is further likely that available data sources are biased in their coverage of sex, race, age, and socioeconomic status (SES). METHODS: Six individual real-world data sources were combined to develop a high-quality composite mortality score. The composite score was benchmarked against the gold standard for mortality data, the National Death Index. Subgroup analyses were then conducted to evaluate the completeness and accuracy by sex, race, age, and SES. RESULTS: The composite mortality score achieved a sensitivity of 94.9% and specificity of 92.8% compared with the National Death Index, with concordance within 1 day of 98.6%. Although some individual data sources show significant coverage gaps related to sex, race, age, and SES, the composite score maintains high sensitivity (84.6%-96.1%) and specificity (77.9%-99.2%) across subgroups. CONCLUSION: A composite score leveraging multiple scalable sources for mortality in the real-world setting maintained strong sensitivity, specificity, and concordance, including across sex, race, age, and SES subgroups.

Seven decades of chemotherapy clinical trials: a pan-cancer social network analysis.

Clinical trials establish the standard of cancer care, yet the evolution and characteristics of the social dynamics between the people conducting this work remain understudied. We performed a social network analysis of authors publishing chemotherapy-based prospective trials from 1946 to 2018 to understand how social influences, including the role of gender, have influenced the growth and development of this network, which has expanded exponentially from fewer than 50 authors in 1946 to 29,197 in 2018. While 99.4% of authors were directly or indirectly connected by 2018, our results indicate a tendency to predominantly connect with others in the same or similar fields, as well as an increasing disparity in author impact and number of connections. Scale-free effects were evident, with small numbers of individuals having disproportionate impact. Women were under-represented and likelier to have lower impact, shorter productive periods (P < 0.001 for both comparisons), less centrality, and a greater proportion of co-authors in their same subspecialty. The past 30 years were characterized by a trend towards increased authorship by women, with new author parity anticipated in 2032. The network of cancer clinical trialists is best characterized as strategic or mixed-motive, with cooperative and competitive elements influencing its appearance. Network effects such as low centrality, which may limit access to high-profile individuals, likely contribute to the observed disparities.

A Phase II Study of Glembatumumab Vedotin for Metastatic Uveal Melanoma.

Glembatumumab vedotin (CDX-011, GV) is a fully human Immunoglobulin G2 monoclonal antibody directed against glycoprotein NMB coupled via a peptide linker to monomethyl auristatin E (MMAE), a potent cytotoxic microtubule inhibitor. This phase II study evaluated the overall response rate and safety of GV, glycoprotein NMB (GPNMB) expression, and survival in patients with metastatic uveal melanoma. Eligible patients with metastatic uveal melanoma who had not previously been treated with chemotherapy received GV 1.9 mg/kg every three weeks. The primary endpoint was the objective response rate (ORR). Secondary endpoints included GPNMB expression, progression-free survival (PFS), overall survival (OS), and toxicity analysis. GPNMB expression was assessed pre- and post-treatment via immunohistochemistry for patients with available tumor tissue. Out of 35 patients who received treatment, two patients had confirmed partial responses (PRs; 6%), and 18 patients had a stable disease (SD; 51%) as the best objective response. 38% of the patients had stable disease >100 days. The grade 3 or 4 toxicities that occurred in two or more patients were neutropenia, rash, hyponatremia, and vomiting. The median progression-free survival was 3.1 months (95% CI: 1.5-5.6), and the median overall survival was 11.9 months (95% CI 9.0-16.9) in the evaluable study population. GV is well-tolerated in metastatic uveal melanoma. The disease control rate was 57% despite a low objective response rate. Exploratory immune correlation studies are underway to provide insight into target saturation, combination strategies, and antigen release.

Pre-Treatment Mutational and Transcriptomic Landscape of Responding Metastatic Melanoma Patients to Anti-PD1 Immunotherapy.

Immunotherapy, such as anti-PD1, has improved the survival of patients with metastatic melanoma. However, predicting which patients will respond to immunotherapy remains a significant knowledge gap. In this study we analyzed pre-immunotherapy treated tumors from 52 patients with metastatic melanoma and monitored their response based on RECIST 1.1 criteria. The responders group contained 21 patients that had a complete or partial response, while the 31 non-responders had stable or progressive disease. Whole exome sequencing (WES) was used to identify biomarkers of anti-PD1 response from somatic mutations between the two groups. Variants in codons G34 and G41 in NFKBIE, a negative regulator of NFkB, were found exclusively in the responders. Mutations in NKBIE-related genes were also enriched in the responder group compared to the non-responders. Patients that harbored NFKBIE-related gene mutations also had a higher mutational burden, decreased tumor volume with treatment, and increased progression-free survival. RNA sequencing on a subset of tumor samples identified that CD83 was highly expressed in our responder group. Additionally, Gene Set Enrichment Analysis showed that the TNFalpha signaling via NFkB pathway was one of the top pathways with differential expression in responders vs. non-responders. In vitro NFkB activity assays indicated that the G34E variant caused loss-of-function of NFKBIE, and resulted in activation of NFkB signaling. Flow cytometry assays indicated that G34E variant was associated with upregulation of CD83 in human melanoma cell lines. These results suggest that NFkB activation and signaling in tumor cells contributes to a favorable anti-PD1 treatment response, and clinical screening to include aberrations in NFkB-related genes should be considered.

Clinical implementation of pharmacogenomics via a health system-wide research biobank: the University of Colorado experience.

In recent years, the genomics community has witnessed the growth of large research biobanks, which collect DNA samples for research purposes. Depending on how and where the samples are genotyped, biobanks also offer the potential opportunity to return actionable genomic results to the clinical setting. We developed a preemptive clinical pharmacogenomic implementation initiative via a health system-wide research biobank at the University of Colorado. Here, we describe how preemptive return of clinical pharmacogenomic results via a research biobank is feasible, particularly when coupled with strong institutional support to maximize the impact and efficiency of biobank resources, a multidisciplinary implementation team, automated clinical decision support tools, and proactive strategies to engage stakeholders early in the clinical decision support tool development process.

A nomogram to predict node positivity in patients with thin melanomas helps inform shared patient decision making.

OBJECTIVE: To develop a nomogram to estimate the probability of positive sentinel lymph node (+SLN) for patients with thin melanoma and to characterize its potential impact on sentinel lymph node biopsy (SLNB) rates. METHODS: Patients diagnosed with thin (0.5-1.0 mm) melanoma were identified from the National Cancer Database 2012 to 2015. A multivariable logistic regression model was used to examine factors associated with +SLN, and a nomogram to predict +SLN was constructed. Nomogram performance was evaluated and diagnostic test statistics were calculated. RESULTS: Of the 21 971 patients included 10 108 (46.0%) underwent SLNB, with a 4.0% +SLN rate. On multivariable analysis, age, Breslow thickness, lymphovascular invasion, ulceration, and Clark level were significantly associated with SLN status. The area under the receiver operating curve was 0.67 (95% confidence interval, 0.65-0.70). While 15 249 (69.4%) patients had either T1b tumors or T1a tumors with at least one adverse feature, only 2846 (13.0%) had a nomogram predicted probability of a +SLN ≥5%. Using this cut-off, the indication for a SLNB in these patients would be reduced by 81.3% as compared to the American Joint Committee on Cancer 8th edition staging criteria. CONCLUSIONS: The risk predictions obtained from the nomogram allow for more accurate selection of patients who could benefit from SLNB.

Poor prognosis for thin ulcerated melanomas and implications for a more aggressive approach to treatment.

BACKGROUND: Clinical guidelines for the treatment of melanoma are based largely on the behavior of thicker tumors. As a result, little is known about survival differences among patients with thinner tumors. OBJECTIVE: To investigate the variability in survival for American Joint Committee on Cancer stage T1 thin melanoma tumors, defined as tumors less than 1 mm thick at diagnosis. METHODS: This population-based series included 43,008 non-Hispanic whites in whom cutaneous melanoma was diagnosed between 2004 and 2013 from the California Cancer Registry. Survival outcomes were estimated using the Kaplan-Meier method. Cox proportional hazard models were used to estimate risk of death. RESULTS: Survival for patients with thin ulcerated tumors was comparable to that for patients with stage II tumors, who are currently treated more aggressively. At 12 months, patients with thin ulcerated tumors had approximately 6% lower survival (92.5% [95% confidence interval (CI), 90.6%-93.9%]) compared with patients with thin nonulcerated tumors (98.2% [95% CI, 98.0%-98.3%]). At 24 months, this survival difference increased (85.2% [95% CI, 82.8%-87.4%] vs 96.1% [95% CI, 95.8-96.3%] for those with thin ulcerated and thin nonulcerated tumors, respectively) and a greater than 15% survival difference was seen at 60 months. LIMITATIONS: Previous reports of cancer registry data have noted some evidence of miscoding of thin tumors. CONCLUSION: The poorer survival in patients with ulcerated tumors less than 1 mm thick implies the need for additional studies to determine potential benefits of more aggressive treatment.

ALK Inhibitor Response in Melanomas Expressing EML4-ALK Fusions and Alternate ALK Isoforms.

Oncogenic ALK fusions occur in several types of cancer and can be effectively treated with ALK inhibitors; however, ALK fusions and treatment response have not been characterized in malignant melanomas. Recently, a novel isoform of ALK (ALKATI ) was reported in 11% of melanomas but the response of melanomas expressing ALKATI to ALK inhibition has not been well characterized. We analyzed 45 melanoma patient-derived xenograft models for ALK mRNA and protein expression. ALK expression was identified in 11 of 45 (24.4%) melanomas. Ten melanomas express wild-type (wt) ALK and/or ALKATI and one mucosal melanoma expresses multiple novel EML4-ALK fusion variants. Melanoma cells expressing different ALK variants were tested for response to ALK inhibitors. Whereas the melanoma expressing EML4-ALK were sensitive to ALK inhibitors in vitro and in vivo, the melanomas expressing wt ALK or ALKATI were not sensitive to ALK inhibitors. In addition, a patient with mucosal melanoma expressing ALKATI was treated with an ALK/ROS1/TRK inhibitor (entrectinib) on a phase I trial but did not respond. Our results demonstrate ALK fusions occur in malignant melanomas and respond to targeted therapy, whereas melanomas expressing ALKATI do not respond to ALK inhibitors. Targeting ALK fusions is an effective therapeutic option for a subset of melanoma patients, but additional clinical studies are needed to determine the efficacy of targeted therapies in melanomas expressing wt ALK or ALKATIMol Cancer Ther; 17(1); 222-31. ©2017 AACR.

Targeted Next Generation Sequencing Identifies Markers of Response to PD-1 Blockade.

Therapeutic antibodies blocking programmed death-1 and its ligand (PD-1/PD-L1) induce durable responses in a substantial fraction of melanoma patients. We sought to determine whether the number and/or type of mutations identified using a next-generation sequencing (NGS) panel available in the clinic was correlated with response to anti-PD-1 in melanoma. Using archival melanoma samples from anti-PD-1/PD-L1-treated patients, we performed hybrid capture-based NGS on 236-315 genes and T-cell receptor (TCR) sequencing on initial and validation cohorts from two centers. Patients who responded to anti-PD-1/PD-L1 had higher mutational loads in an initial cohort (median, 45.6 vs. 3.9 mutations/MB; P = 0.003) and a validation cohort (37.1 vs. 12.8 mutations/MB; P = 0.002) compared with nonresponders. Response rate, progression-free survival, and overall survival were superior in the high, compared with intermediate and low, mutation load groups. Melanomas with NF1 mutations harbored high mutational loads (median, 62.7 mutations/MB) and high response rates (74%), whereas BRAF/NRAS/NF1 wild-type melanomas had a lower mutational load. In these archival samples, TCR clonality did not predict response. Mutation numbers in the 315 genes in the NGS platform strongly correlated with those detected by whole-exome sequencing in The Cancer Genome Atlas samples, but was not associated with survival. In conclusion, mutational load, as determined by an NGS platform available in the clinic, effectively stratified patients by likelihood of response. This approach may provide a clinically feasible predictor of response to anti-PD-1/PD-L1. Cancer Immunol Res; 4(11); 959-67. ©2016 AACR.

Pragmatic precision oncology: the secondary uses of clinical tumor molecular profiling.

BACKGROUND: Precision oncology increasingly utilizes molecular profiling of tumors to determine treatment decisions with targeted therapeutics. The molecular profiling data is valuable in the treatment of individual patients as well as for multiple secondary uses. OBJECTIVE: To automatically parse, categorize, and aggregate clinical molecular profile data generated during cancer care as well as use this data to address multiple secondary use cases. METHODS: A system to parse, categorize and aggregate molecular profile data was created. A naÿve Bayesian classifier categorized results according to clinical groups. The accuracy of these systems were validated against a published expertly-curated subset of molecular profiling data. RESULTS: Following one year of operation, 819 samples have been accurately parsed and categorized to generate a data repository of 10,620 genetic variants. The database has been used for operational, clinical trial, and discovery science research. CONCLUSIONS: A real-time database of molecular profiling data is a pragmatic solution to several knowledge management problems in the practice and science of precision oncology.

SMART precision cancer medicine: a FHIR-based app to provide genomic information at the point of care.

BACKGROUND: Precision cancer medicine (PCM) will require ready access to genomic data within the clinical workflow and tools to assist clinical interpretation and enable decisions. Since most electronic health record (EHR) systems do not yet provide such functionality, we developed an EHR-agnostic, clinico-genomic mobile app to demonstrate several features that will be needed for point-of-care conversations. METHODS: Our prototype, called Substitutable Medical Applications and Reusable Technology (SMART)® PCM, visualizes genomic information in real time, comparing a patient's diagnosis-specific somatic gene mutations detected by PCR-based hotspot testing to a population-level set of comparable data. The initial prototype works for patient specimens with 0 or 1 detected mutation. Genomics extensions were created for the Health Level Seven® Fast Healthcare Interoperability Resources (FHIR)® standard; otherwise, the prototype is a normal SMART on FHIR app. RESULTS: The PCM prototype can rapidly present a visualization that compares a patient's somatic genomic alterations against a distribution built from more than 3000 patients, along with context-specific links to external knowledge bases. Initial evaluation by oncologists provided important feedback about the prototype's strengths and weaknesses. We added several requested enhancements and successfully demonstrated the app at the inaugural American Society of Clinical Oncology Interoperability Demonstration; we have also begun to expand visualization capabilities to include cancer specimens with multiple mutations. DISCUSSION: PCM is open-source software for clinicians to present the individual patient within the population-level spectrum of cancer somatic mutations. The app can be implemented on any SMART on FHIR-enabled EHRs, and future versions of PCM should be able to evolve in parallel with external knowledge bases.

Implementing and Improving Automated Electronic Tumor Molecular Profiling.

Oncology practice increasingly requires the use of molecular profiling of tumors to inform the use of targeted therapeutics. However, many oncologists use third-party laboratories to perform tumor genomic testing, and these laboratories may not have electronic interfaces with the provider's electronic medical record (EMR) system. The resultant reporting mechanisms, such as plain-paper faxing, can reduce report fidelity, slow down reporting procedures for a physician's practice, and make reports less accessible. Vanderbilt University Medical Center and its genomic laboratory testing partner have collaborated to create an automated electronic reporting system that incorporates genetic testing results directly into the clinical EMR. This system was iteratively tested, and causes of failure were discovered and addressed. Most errors were attributable to data entry or typographical errors that made reports unable to be linked to the correct patient in the EMR. By providing direct feedback to providers, we were able to significantly decrease the rate of transmission errors (from 6.29% to 3.84%; P < .001). The results and lessons of 1 year of using the system and transmitting 832 tumor genomic testing reports are reported.

Advances in website information resources to aid in clinical practice.

The World Wide Web, which has been widely implemented for roughly two decades, is humankind's most impressive effort to aggregate and organize knowledge to date. The medical community was slower to embrace the Internet than others, but the majority of clinicians now use it as part of their everyday practice. For the practicing oncologist, there is a daunting quantity of information to master. For example, a new article relating to cancer is added to the MEDLINE database approximately every 3 minutes. Fortunately, Internet resources can help organize the deluge of information into useful knowledge. This manuscript provides an overview of resources related to general medicine, oncology, and social media that will be of practical use to the practicing oncologist. It is clear from the vast size of the Internet that we are all life-long learners, and the challenge is to acquire "just-in-time" information so that we can provide the best possible care to our patients. The resources that we have presented in this article should help the practicing oncologist continue along the path of transforming information to knowledge to wisdom.

Immune checkpoint inhibitors in NSCLC.

OPINION STATEMENT: Lung cancer is the leading cause of cancer-related mortality worldwide. Cytotoxic chemotherapy and tyrosine kinase inhibitors provide palliation and prolong survival, however, the median survival for patients with metastatic disease remains poor and more effective therapies are needed. Immune checkpoint inhibitors have shown promising results in phase I trials and are being evaluated in ongoing clinical trials in both small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) patients. These include agents targeting the programmed cell death-1 receptor and its ligand (PD-1/PD-L1; notably nivolumab, pembrolizumab, MPDL3280A, and MEDI-4736) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4; ipilimumab and tremelimumab); these agents induce antitumor responses by inhibiting critical negative T cell regulators. In particular, the anti-PD-1/PD-L1 therapies administered as single agent therapy in chemotherapy refractory patients have produced objective response rates ranging from 15 %-25 %, the majority of which were rapid and ongoing 1 year after starting therapy. Furthermore, the toxicity profile for these agents differs from that of cytotoxic chemotherapy but generally is much better tolerated. Promising biomarkers, particularly tumor expression of PD-L1 and tumor infiltrating lymphocytes, may aid in treatment selection and stratification. Ongoing evaluation is needed to define the most appropriate timing and patient population that will benefit from therapy with an immune checkpoint inhibitors and the role of combining these agents with existing therapies including systemic therapy and radiation.

Targeted deletion of the calcineurin inhibitor DSCR1 suppresses tumor growth.

The NF-AT transcription factors regulated by the phosphatase calcineurin play a role in breast cancer metastasis-promoting tumor cell invasion. Metastasis is a multistep process requiring angiogenesis and endothelial activation. NF-AT is also expressed in endothelial cells, and calcineurin-NF-AT signaling is an important downstream effector of the proangiogenic cytokine VEGF. One isoform of the endogenous calcineurin regulator, Down syndrome candidate region-1 (DSCR1.Ex4), suppresses calcineurin-NFAT signaling blocking endothelial proliferation. However, overexpression of the other DSCR1 isoform (DSCR1.Ex1) may promote angiogenesis. We report that targeted deletion of both isoforms leads to hyperactivated calcineurin and precocious endothelial apoptosis, inhibiting formation of an effective tumor vasculature and suppressing tumorigenesis. Treatment with the specific pharmacological calcineurin inhibitor cyclosporin A rescues this endothelial defect in DSCR1(-/-) mice, restoring tumor growth.