Evaluating CD133 as a Radiotheranostic Target in Small-Cell Lung Cancer.

Despite decades of work, small-cell lung cancer (SCLC) remains a frustratingly recalcitrant disease. Both diagnosis and treatment are challenges: low-dose computed tomography (the approved method used for lung cancer screening) is unable to reliably detect early SCLC, and the malignancy's 5 year survival rate stands at a paltry 7%. Clearly, the development of novel diagnostic and therapeutic tools for SCLC is an urgent, unmet need. CD133 is a transmembrane protein that is expressed at low levels in normal tissue but is overexpressed by a variety of tumors, including SCLC. We previously explored CD133 as a biomarker for a novel autoantibody-to-immunopositron emission tomography (PET) strategy for the diagnosis of SCLC, work that first suggested the promise of the antigen as a radiotheranostic target in the disease. Herein, we report the in vivo validation of a pair of CD133-targeted radioimmunoconjugates for the PET imaging and radioimmunotherapy of SCLC. To this end, [89Zr]Zr-DFO-αCD133 was first interrogated in a trio of advanced murine models of SCLC─i.e., orthotopic, metastatic, and patient-derived xenografts─with the PET probe consistently producing high activity concentrations (>%ID/g) in tumor lesions combined with low uptake in healthy tissues. Subsequently, a variant of αCD133 labeled with the ß-emitting radiometal 177Lu─[177Lu]Lu-DTPA-A″-CHX-αCD133─was synthesized and evaluated in a longitudinal therapy study in a subcutaneous xenograft model of SCLC, ultimately revealing that treatment with a dose of 9.6 MBq of the radioimmunoconjugate produced a significant increase in median survival compared to a control cohort. Taken together, these data establish CD133 as a viable target for the nuclear imaging and radiopharmaceutical therapy of SCLC.

Phosphorylation of connexin 43 at MAPK, PKC or CK1 sites each distinctly alter the kinetics of epidermal wound repair.

The gap junction protein connexin 43 (Cx43) is a key player in wound healing, and inhibitors of Cx43, which speed epidermal wound healing, are currently in clinical trials. Here, we provide direct in vivo evidence that specific phosphorylation events on Cx43 change the physiological response during wound healing. Blocking phosphorylation, through mutation of serine residues in Cx43 at the protein kinase C (PKC) or casein kinase 1 (CK1) sites, significantly slowed the rate of wound closure in vivo and in vitro and resulted in a thicker epidermal layer after reepithelialization. Conversely, preventing Cx43 phosphorylation by mitogen-activated protein kinases (MAPKs) through mutation significantly increased the rate of wound closure in vivo Defects in migration, but not proliferation, in all mutants were partially rescued in vitro by changing serine residues to aspartic or glutamic acid. These data prove that specific Cx43 phosphorylation events play an important role at different stages of wound healing. Thus, a clear physiological understanding of the spatiotemporal regulation of kinase activation and consequent effects on gap junctions could lead to a more targeted approach to modulating Cx43 expression during wound healing.

Tumor-derived Autoantibodies Identify Malignant Pulmonary Nodules.

Rationale: Screening for non-small cell lung cancer is associated with earlier diagnosis and reduced mortality but also increased harm caused by invasive follow-up of benign pulmonary nodules. Lung tumorigenesis activates the immune system, components of which could serve as tumor-specific biomarkers. Objectives: To profile tumor-derived autoantibodies as peripheral biomarkers of malignant pulmonary nodules. Methods: High-density protein arrays were used to define the specificity of autoantibodies isolated from B cells of 10 resected lung tumors. These tumor-derived autoantibodies were also examined as free or complexed to antigen in the plasma of the same 10 patients and matched benign nodule control subjects. Promising autoantibodies were further analyzed in an independent cohort of 250 nodule-positive patients. Measurements and Main Results: Thirteen tumor B-cell-derived autoantibodies isolated ex vivo showed greater than or equal to 50% sensitivity and greater than or equal to 70% specificity for lung cancer. In plasma, 11 of 13 autoantibodies were present both complexed to and free from antigen. In the larger validation cohort, 5 of 13 tumor-derived autoantibodies remained significantly elevated in cancers. A combination of four of these autoantibodies could detect malignant nodules with an area under the curve of 0.74 and had an area under the curve of 0.78 in a subcohort of indeterminate (8-20 mm in the longest diameter) pulmonary nodules. Conclusions: Our novel pipeline identifies tumor-derived autoantibodies that could effectively serve as blood biomarkers for malignant pulmonary nodule diagnosis. This approach has future implications for both a cost-effective and noninvasive approach to determine nodule malignancy for widespread low-dose computed tomography screening.

Comparison of prediction models with radiological semantic features and radiomics in lung cancer diagnosis of the pulmonary nodules: a case-control study.

PURPOSE: To compare the ability of radiological semantic and quantitative texture features in lung cancer diagnosis of pulmonary nodules. MATERIALS AND METHODS: A total of N = 121 subjects with confirmed non-small-cell lung cancer were matched with 117 controls based on age and gender. Radiological semantic and quantitative texture features were extracted from CT images with or without contrast enhancement. Three different models were compared using LASSO logistic regression: "CS" using clinical and semantic variables, "T" using texture features, and "CST" using clinical, semantic, and texture variables. For each model, we performed 100 trials of fivefold cross-validation and the average receiver operating curve was accessed. The AUC of the cross-validation study (AUCCV) was calculated together with its 95% confidence interval. RESULTS: The AUCCV (and 95% confidence interval) for models T, CS, and CST was 0.85 (0.71-0.96), 0.88 (0.77-0.96), and 0.88 (0.77-0.97), respectively. After separating the data into two groups with or without contrast enhancement, the AUC (without cross-validation) of the model T was 0.86 both for images with and without contrast enhancement, suggesting that contrast enhancement did not impact the utility of texture analysis. CONCLUSIONS: The models with semantic and texture features provided cross-validated AUCs of 0.85-0.88 for classification of benign versus cancerous nodules, showing potential in aiding the management of patients. KEY POINTS: • Pretest probability of cancer can aid and direct the physician in the diagnosis and management of pulmonary nodules in a cost-effective way. • Semantic features (qualitative features reported by radiologists to characterize lung lesions) and radiomic (e.g., texture) features can be extracted from CT images. • Input of these variables into a model can generate a pretest likelihood of cancer to aid clinical decision and management of pulmonary nodules.

Proteomic Analysis, Immune Dysregulation, and Pathway Interconnections with Obesity.

Proteomic studies can offer information on hundreds to thousands of proteins and potentially provide researchers with a comprehensive understanding of signaling response during stress and disease. Large data sets, such as those obtained in high-dimensional proteomic studies, can be leveraged for pathway analysis to discover or describe the biological implications of clinical disease states. Obesity is a worldwide epidemic that is considered a risk factor for numerous other diseases. We performed analysis on plasma proteomic data from 3 separate sample sets of postmenopausal women to identify the pathways that are altered in subjects with a high body mass index (BMI) compared to normal BMI. We found many pathways consistently and significantly associated with inflammation dysregulated in plasma from obese/overweight subjects compared to plasma from normal BMI subjects. These pathways indicate alterations of soluble inflammatory regulators, cellular stress, and metabolic dysregulation. Our results highlight the importance of high-dimensional pathway analysis in complex diseases as well as provide information on the interconnections between pathways that are dysregulated with obesity. Specifically, overlap of obesity related pathways with those activated during cancer and infection could help describe why obesity is a risk factor for disease and help devise treatment options that mitigate its effect.

Breaking tolerance: autoantibodies can target protein posttranslational modifications.

Autoantibodies (AAb) are an immunological resource ripe for exploitation in cancer detection and treatment. Key to this translation is a better understanding of the self-epitope that AAb target in tumor tissue, but do not bind to in normal tissue. Posttranslational modifications (PTMs) on self-proteins are known to break tolerance in many autoimmune diseases and have also recently been described in cancer. This scope of possible autoantigens is quite broad and new high-dimensional and -throughput technologies to probe this repertoire will be necessary to fully exploit their potential. Here, we discuss the strengths and weaknesses of existing high-throughput platforms to detect AAb, review the current methods for characterizing immunogenic PTMs, describe the main challenges to identifying disease-relevant antigens and suggest the properties of future technologies that may be able to address these challenges. We conclude that exploiting the evolutionary power of the immune system to distinguish between self and nonself has great potential to be translated into antibody-based clinical applications.

Multi-Omic Biomarkers Improve Indeterminate Pulmonary Nodule Malignancy Risk Assessment.

The clinical management of patients with indeterminate pulmonary nodules is associated with unintended harm to patients and better methods are required to more precisely quantify lung cancer risk in this group. Here, we combine multiple noninvasive approaches to more accurately identify lung cancer in indeterminate pulmonary nodules. We analyzed 94 quantitative radiomic imaging features and 41 qualitative semantic imaging variables with molecular biomarkers from blood derived from an antibody-based microarray platform that determines protein, cancer-specific glycan, and autoantibody-antigen complex content with high sensitivity. From these datasets, we created a PSR (plasma, semantic, radiomic) risk prediction model comprising nine blood-based and imaging biomarkers with an area under the receiver operating curve (AUROC) of 0.964 that when tested in a second, independent cohort yielded an AUROC of 0.846. Incorporating known clinical risk factors (age, gender, and smoking pack years) for lung cancer into the PSR model improved the AUROC to 0.897 in the second cohort and was more accurate than a well-characterized clinical risk prediction model (AUROC = 0.802). Our findings support the use of a multi-omics approach to guide the clinical management of indeterminate pulmonary nodules.

Posttranslational modifications induce autoantibodies with risk prediction capability in patients with small cell lung cancer.

Small cell lung cancer (SCLC) elicits the generation of autoantibodies that result in unique paraneoplastic neurological syndromes. The mechanistic basis for the formation of such autoantibodies is largely unknown but is key to understanding their etiology. We developed a high-dimensional technique that enables detection of autoantibodies in complex with native antigens directly from patient plasma. Here, we used our platform to screen 1009 human plasma samples for 3600 autoantibody-antigen complexes, finding that plasma from patients with SCLC harbors, on average, fourfold higher disease-specific autoantibody signals compared with plasma from patients with other cancers. Across three independent SCLC cohorts, we identified a set of common but previously unknown autoantibodies that are produced in response to both intracellular and extracellular tumor antigens. We further characterized several disease-specific posttranslational modifications within extracellular proteins targeted by these autoantibodies, including citrullination, isoaspartylation, and cancer-specific glycosylation. Because most patients with SCLC have metastatic disease at diagnosis, we queried whether these autoantibodies could be used for SCLC early detection. We created a risk prediction model using five autoantibodies with an average area under the curve of 0.84 for the three cohorts that improved to 0.96 by incorporating cigarette smoke consumption in pack years. Together, our findings provide an innovative approach to identify circulating autoantibodies in SCLC with mechanistic insight into disease-specific immunogenicity and clinical utility.

CD133 as a Biomarker for an Autoantibody-to-ImmunoPET Paradigm for the Early Detection of Small Cell Lung Cancer.

Small cell lung cancer (SCLC) is a deadly neuroendocrine tumor for which there are no screening methods sensitive enough to facilitate early, effective intervention. We propose targeting the neuroendocrine tumor neoantigen CD133 via antibody-based early detection and PET (immunoPET) to facilitate earlier and more accurate detection of SCLC. Methods: RNA sequencing datasets, immunohistochemistry, flow cytometry, and Western blots were used to quantify CD133 expression in healthy and SCLC patients. CD133 was imaged in vivo using near-infrared fluorescence (NIRF) immunoimaging, and 89Zr immunoPET. Anti(α)-CD133 autoantibody levels were measured in SCLC patient plasma using antibody microarrays. Results: Across 6 publicly available datasets, CD133 messenger RNA was found to be higher in SCLC tumors than in other tissues, including healthy or normal adjacent lung and non-SCLC samples. Critically, the upregulation of CD133 messenger RNA in SCLC was associated with a significant increase (hazard ratio, 2.62) in death. CD133 protein was expressed in primary human SCLC, in SCLC patient-derived xenografts, and in both SCLC cell lines tested (H82 and H69). Using an H82 xenograft mouse model, we first imaged CD133 expression with NIRF. Both in vivo and ex vivo NIRF clearly showed that a fluorophore-tagged αCD133 homed to lung tumors. Next, we validated the noninvasive visualization of subcutaneous and orthotopic H82 xenografts via immunoPET. An αCD133 antibody labeled with the positron-emitting radiometal 89Zr demonstrated significant accumulation in tumor tissue while producing minimal uptake in healthy organs. Finally, plasma αCD133 autoantibodies were found in subjects from cohort studies up to 1 year before SCLC diagnosis. Conclusion: In light of these findings, we conclude that the presence of αCD133 autoantibodies in a blood sample followed by CD133-targeted 89Zr-immunoPET could be an effective early detection screening strategy for SCLC.

Resistance mechanisms to genetic suppression of mutant NRAS in melanoma.

Targeted therapies have revolutionized cancer care, but the development of resistance remains a challenge in the clinic. To identify rational targets for combination strategies, we used an established melanoma mouse model and selected for resistant tumors following genetic suppression of NRAS expression. Complete tumor regression was observed in all mice, but 40% of tumors recurred. Analysis of resistant tumors showed that the most common mechanism of resistance was overexpression and activation of receptor tyrosine kinases (RTKs). Interestingly, the most commonly overexpressed RTK was Met and inhibition of Met overcame NRAS resistance in this context. Analysis of NRAS mutant human melanoma cells showed enhanced efficacy of cytotoxicity with combined RTK and mitogen-activated protein kinase kinase inhibition. In this study, we establish the importance of adaptive RTK signaling in the escape of NRAS mutant melanoma from inhibition of RAS and provide the rationale for combined blockade of RAS and RTK signaling in this context.

Control of PD-L1 Expression by Oncogenic Activation of the AKT-mTOR Pathway in Non-Small Cell Lung Cancer.

Alterations in EGFR, KRAS, and ALK are oncogenic drivers in lung cancer, but how oncogenic signaling influences immunity in the tumor microenvironment is just beginning to be understood. Immunosuppression likely contributes to lung cancer, because drugs that inhibit immune checkpoints like PD-1 and PD-L1 have clinical benefit. Here, we show that activation of the AKT-mTOR pathway tightly regulates PD-L1 expression in vitro and in vivo. Both oncogenic and IFNγ-mediated induction of PD-L1 was dependent on mTOR. In human lung adenocarcinomas and squamous cell carcinomas, membranous expression of PD-L1 was significantly associated with mTOR activation. These data suggest that oncogenic activation of the AKT-mTOR pathway promotes immune escape by driving expression of PD-L1, which was confirmed in syngeneic and genetically engineered mouse models of lung cancer where an mTOR inhibitor combined with a PD-1 antibody decreased tumor growth, increased tumor-infiltrating T cells, and decreased regulatory T cells.

Akt signaling accelerates tumor recurrence following ras inhibition in the context of ink4a/arf loss.

Aberrant activation of the RAS signaling pathway contributes to nearly all human cancers, including gliomas. To determine the dependence of high-grade gliomas on this signaling pathway, we developed a doxycycline-regulated KRas glioma mouse model. Using this model we previously demonstrated that inhibition of KRas expression in gliomas induced by activated KRas and Akt results in complete tumor regression. We have also shown that, in the context of Ink4a/Arf loss, abrogation of KRas signaling is sufficient to decrease tumor burden but resistance ensues. In this study, we sought to determine the effect of activated Akt signaling in combination with activated KRas and loss of Ink4a/Arf on the growth and recurrence of brain tumors following suppression of KRas expression. We observed significant tumor formation in Ink4a/Arf(lox/lox) mice injected with retroviruses containing tetracycline responsive element (TRE)-KRas, Tet-off, Akt, and Cre. Abrogation of KRas signaling resulted in significant tumor regression; however, resistance developed after a relatively short latency. Tumor recurrence occurred more rapidly and the tumors were more aggressive in the presence of activated Akt signaling compared with loss of Ink4a/Arf alone suggesting that this pathway contributes to tumor progression in this context.

Ink4a/Arf loss promotes tumor recurrence following Ras inhibition.

Aberrant activation of rat sarcoma (Ras) signaling contributes to the development of a variety of human cancers, including gliomas. To determine the dependence of high-grade gliomas on continued Ras signaling, we developed a doxycycline-regulated Kirsten Ras (KRas) glioma mouse model. We previously demonstrated that KRas is required for the maintenance of glioblastoma multiforme tumors arising in the context of activated Akt signaling in vivo; inhibition of KRas expression resulted in apoptotic tumor regression and significantly increased survival. We utilized a well-established glioma mouse model to determine the reliance of gliomas on continued KRas signaling in the context of Ink4a/Arf deficiency, a common occurrence in human gliomas. Despite the dependency of primary gliomas on continued KRas signaling, a significant percentage of tumors progressed to a KRas-independent state in the absence of Ink4a/Arf expression, demonstrating that these tumor suppressors play a critical role in the suppression of glioma recurrence. While even advanced stages of gliomas may remain dependent upon KRas signaling for maintenance and growth, our findings demonstrate that loss of Ink4a/Arf facilitates the acquisition of oncogene independence and tumor recurrence. Furthermore, reactivation of the Ras mitogen-activated protein kinase pathway in the absence of virally delivered KRas expression is a common mechanism of recurrence in this context.

Targeted delivery of NRASQ61R and Cre-recombinase to post-natal melanocytes induces melanoma in Ink4a/Arflox/lox mice.

We have developed a somatic cell gene delivery mouse model of melanoma that allows for the rapid validation of genetic alterations identified in this disease. A major advantage of this system is the ability to model the multi-step process of carcinogenesis in immune-competent mice without the generation and cross breeding of multiple strains. We have used this model to evaluate the role of RAS isoforms in melanoma initiation in the context of conditional Ink4a/Arf loss. Mice expressing the tumor virus A (TVA) receptor specifically in melanocytes under control of the dopachrome tautomerase (DCT) promoter were crossed to Ink4a/Arf(lox/lox) mice and newborn DCT-TVA/Ink4a/Arf(lox/lox) mice were injected with retroviruses containing activated KRAS, NRAS and/or Cre-recombinase. No mice injected with viruses containing KRAS and Cre or NRAS alone developed tumors; however, more than one-third of DCT-TVA/Ink4a/Arf(lox/lox) mice injected with NRAS and Cre viruses developed melanoma and two-thirds developed melanoma when NRAS and Cre expression was linked.