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One pivotal feature of transcriptomics data is the unwanted variations caused by disparate experimental handling, known as handling effects. Various data normalization methods were developed to alleviate the adverse impact of handling effects in the setting of differential expression analysis. However, little research has been done to evaluate their performance in the setting of survival outcome prediction, an important analysis goal for transcriptomics data in biomedical research. Leveraging a unique pair of datasets for the same set of tumor samples-one with handling effects and the other without, we developed a benchmarking tool for conducting such an evaluation in microRNA microarrays. We applied this tool to evaluate the performance of three popular normalization methods-quantile normalization, median normalization and variance stabilizing normalization-in survival prediction using various approaches for model building and designs for sample assignment. We showed that handling effects can have a strong impact on survival prediction and that quantile normalization, a most popular method in current practice, tends to underperform median normalization and variance stabilizing normalization. We demonstrated with a small example the reason for quantile normalization's poor performance in this setting. Our finding highlights the importance of putting normalization evaluation in the context of the downstream analysis setting and the potential of improving the development of survival predictors by applying median normalization. We make available our benchmarking tool for performing such evaluation on additional normalization methods in connection with prediction modeling approaches., (© The Author(s) 2021. Published by Oxford University Press.)

Scope: Cancer cachexia is characterized by the loss of skeletal muscle resulting in functional impairment, reduced quality of life and mortality. Naringenin, a flavonoid found in citrus fruits, improves insulin sensitivity and reduces inflammation and tumor growth in preclinical models. Therefore, the study hypothesizes that dietary supplementation of naringenin will improve insulin sensitivity, decrease inflammation, slow body weight loss, and delay tumor growth in a mouse model of cancer cachexia., Methods and Results: Mice are fed 2 wt% dietary naringenin before and during initiation of cancer cachexia using inoculated adenocarcinoma-26 cells (C-26). Food intake, body weight, body composition, muscle function, insulin tolerance, and inflammatory status are assessed. Although naringenin-fed tumor-bearing mice exhibit reductions in body weight and food intake earlier than control diet-fed tumor-bearing mice, dietary naringenin is protective against loss of muscle strength, and attenuates the onset of insulin resistance and markers of inflammation., Conclusions: Dietary supplementation of naringenin improves multiple aspects of metabolic disturbance and inflammation during cancer cachexia progression in [C-26 tumor-bearing] mice. However, the acceleration of anorexia and weight loss is also observed. These findings emphasize the link between inflammation and insulin resistance as a basis for understanding their roles in the pathogenesis of cancer cachexia., (© 2021 Wiley-VCH GmbH.)

Purpose: With the emergence of COVID-19, and the potential inclusion of dental benefits in Medicare, it is critical that dentists are able to engage in legislative advocacy to support public oral health. Dental education has an opportunity to teach advocacy skills to future dentists, although advocacy training in predoctoral dental education has been largely ignored. The purpose of this study was to evaluate fourth-year dental student's attitudes toward advocacy, identify the type and extent of advocacy experiences during dental school, and assess their future intentions to engage in advocacy. Methods: An electronic questionnaire was administered to fourth-year dental students enrolled in their final semester at Ohio State University. Results: Forty-seven students completed the survey (43% response rate). Most (84%) respondents agreed that advocacy training should be a required experience in accreditation standards for predoctoral dental education. Over half (58%) reported seldom or no exposure to legislative and regulatory processes in oral health policy development in the curriculum. Students who participated in grassroots advocacy efforts while in dental school were more likely to contact legislators regarding dental issues ( p = 0.005) or public insurance ( p = 0.037), and participate in future lobbying efforts ( p = 0.019). Students who contributed to PAC while in dental school were more likely to express intentions to contribute in future ( p = 0.005). Conclusions: There is limited exposure to legislative advocacy in predoctoral dental education. Dental students with advocacy experience are more likely to report intentions to participate in advocacy as dentists. Dental education has a critical role in preparing future dentist-advocates., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Amini, Wells, Boynton, Guo and Ni.)

Background: The oral microbiota is acquired very early, but the factors shaping its acquisition are not well understood. Previous studies comparing monozygotic (MZ) and dizygotic (DZ) twins have suggested that host genetics plays a role. However, all twins share an equal portion of their parent's genome, so this model is not informative for studying parent-to-child transmission. We used a novel study design that allowed us to directly examine the genetics of transmission by comparing the oral microbiota of biological versus adoptive mother-child dyads., Results: No difference was observed in how closely oral bacterial community profiles matched for adoptive versus biological mother-child pairs, indicating little if any effect of host genetics on the fidelity of transmission. Both adopted and biologic children more closely resembled their own mother as compared to unrelated women, supporting the role of contact and environment. Mother-child strain similarity increased with the age of the child, ruling out early effects of host genetic influence that are lost over time. No effect on the fidelity of mother-child strain sharing from vaginal birth or breast feeding was seen. Analysis of extended families showed that fathers and mothers were equally similar to their children, and that cohabitating couples showed even greater strain similarity than mother-child pairs. These findings support the role of contact and shared environment, and age, but not genetics, as determinants of microbial transmission, and were consistent at both species and strain level resolutions, and across multiple oral habitats. In addition, analysis of individual species all showed similar results., Conclusions: The host is clearly active in shaping the composition of the oral microbiome, since only a few of the many bacterial species in the larger environment are capable of colonizing the human oral cavity. Our findings suggest that these host mechanisms are universally shared among humans, since no effect of genetic relatedness on fidelity of microbial transmission could be detected. Instead our findings point towards contact and shared environment being the driving factors of microbial transmission, with a unique combination of these factors ultimately shaping the highly personalized human oral microbiome. Video abstract.

With the increasing availability of large scale biomedical and -omics data, researchers are offered with unprecedented opportunities to discover novel biomarkers for clinical outcomes. At the same time, they are also faced with great challenges to accurately identify important biomarkers from numerous candidates. Many novel statistical methodologies have been developed to tackle these challenges in the last couple of decades. When the clinical outcome is time-to-event data, special statistical methods are needed to analyze this type of data due to the presence of censoring. In this article, we review some of the most commonly used modern statistical methodologies for variable selection for time-to-event data. The reviewed methods are classified into three large categories: filter-test based method, penalized regression method, and machine learning method.

ZD55-IL-24 is similar but superior to the oncolytic adenovirus ONYX-015, yet the exact mechanism underlying the observed therapeutic effect is still not well understood. Here we sought to elucidate the underlying antitumor mechanism of ZD55-IL-24 in both immunocompetent and immunocompromised mouse model. We find that ZD55-IL-24 eradicates established melanoma in B16-bearing immunocompetent mouse model not through the classic direct killing pathway, but mainly through the indirect pathway of inducing systemic antitumor immunity. Inconsistent with the current prevailing view, our further results suggest that ZD55-IL-24 can induce antitumor immunity in B16-bearing immunocompetent mouse model in fact not due to its ability to lyse tumor cells and release the essential elements, such as tumor-associated antigens (TAAs), but due to its ability to put a "nonself" label in tumor cells and then turn the tumor cells from the "self" state into the "nonself" state without tumor cell death. The observed anti-melanoma efficacy of ZD55-IL-24 in B16-bearing immunocompetent mouse model was practically caused only by the viral vector. In addition, we also notice that ZD55-IL-24 can inhibit tumor growth in B16-bearing immunocompetent mouse model through inhibiting angiogenesis, despite it plays only a minor role. In contrast to B16-bearing immunocompetent mouse model, ZD55-IL-24 eliminates established melanoma in A375-bearing immunocompromised mouse model mainly through the classic direct killing pathway, but not through the antitumor immunity pathway and anti-angiogenesis pathway. These findings let us know ZD55-IL-24 more comprehensive and profound, and provide a sounder theoretical foundation for its future modification and drug development.

Purpose: Gemcitabine and albumin-bound paclitaxel (ABP) exhibit synergistic antitumor efficacy, with ABP serving to increase the intratumoral gemcitabine concentration. Both drugs are active in squamous cell lung cancers (SQCLC) and are conventional partners for carboplatin. We hypothesized that combining gemcitabine and ABP would enhance the antitumor activity in patients with advanced SQCLCs., Patients and Methods: This was a Simon two-stage, open-label, single-arm, multicenter phase II study that enrolled patients between August 1, 2015 and June 1, 2018. We enrolled 37 patients with chemotherapy-naïve, PD-L1 low/unknown advanced stage IV SQCLC. Patients were administered weekly intravenous gemcitabine (1,000 mg/m 2 ) plus ABP (100 mg/m 2 ) in a 3-week on, 1-week off schedule during stage I and a 2-week on, 1-week off schedule in stage II. The primary endpoint was best objective response rate (ORR). Next-generation sequencing by MSK-IMPACT was used to calculate tumor mutation burden and genome doubling and assess somatic variants for correlations with efficacy., Results: Thirty-two patients were evaluable for response assessment. The study satisfied its primary endpoint, with confirmed partial responses in 18 of 32 patients and a complete response in 1 patient [ORR 59%; 95% confidence interval (CI), 42%-74%]. Median progression-free survival (PFS), a secondary endpoint, was 7.5 (95% CI, 6.7-10.5) months. There were no unexpected toxicities., Conclusions: Gemcitabine plus ABP was a safe, tolerable, and effective first-line therapy for patients with chemotherapy-naïve SQCLCs, with an ORR and median PFS substantially higher than carboplatin doublet regimens and efficacy comparable with carboplatin plus taxane plus pembrolizumab., (©2020 American Association for Cancer Research.)

V-domain Ig-containing suppressor of T-cell activation (VISTA) is an immune checkpoint gene that inhibits anti-tumor immune responses. Since most malignant pleural mesotheliomas do not respond to anti-programmed cell death(-ligand)1 (PD-(L)1)/cytotoxic T-lymphocyte-associated protein 4 (CTLA4) therapy and given the recent finding of The Cancer Genome Atlas Study that pleural mesothelioma displays the highest expression of VISTA among all cancers studied, we examined VISTA expression in a large pleural mesothelioma cohort. VISTA and PD-L1 immunohistochemistry were performed on tissue microarray of immunotherapy-naive pleural mesotheliomas (254 epithelioid, 24 biphasic and 41 sarcomatoid) and ten whole-tissue sections of benign pleura (VISTA only). Percentages of tumor and inflammatory cells with positive staining were assessed. Optimal prognostic cutoff percentages were determined using maximally selected rank statistics. Overall survival was evaluated using Kaplan-Meier methods and Cox proportional hazard analysis. All benign mesothelium expressed VISTA. Eighty-five percent of 319 and 38% of 304 mesotheliomas expressed VISTA and PD-L1 (88% and 33% of epithelioid, 90% and 43% of biphasic, and 42% and 75% of sarcomatoid), respectively. Median VISTA score was significantly higher in epithelioid (50%) (vs. biphasic [20%] and sarcomatoid [0]) (p < 0.001), while median PD-L1 score was significantly higher in sarcomatoid tumors (20%) (vs. biphasic and epithelioid [both 0%]) (p < 0.001). VISTA and PD-L1 were expressed in inflammatory cells in 94% (n = 317) and 24% (n = 303) of mesothelioma, respectively. Optimal prognostic cutoffs for VISTA and PD-L1 were 40% and 30%, respectively. On multivariable analysis, VISTA and PD-L1 expression in mesothelioma were associated with better and worse overall survival (p = 0.001 and p = 0.002), respectively, independent of histology. In a large cohort of mesothelioma, we report frequent expression of VISTA and infrequent expression of PD-L1 with favorable and unfavorable survival correlations, respectively. These findings may explain poor responses to anti-PD-(L)1 immunotherapy and suggest VISTA as a potential novel target in pleural mesothelioma.

High-dose chemotherapy and autologous stem cell transplantation (HDT-ASCT) is the standard of care for relapsed or primary refractory (rel/ref) chemorefractory diffuse large B-cell lymphoma. Only 50% of patients are cured with this approach. We investigated safety and efficacy of CD19-specific chimeric antigen receptor (CAR) T cells administered following HDT-ASCT. Eligibility for this study includes poor-risk rel/ref aggressive B-cell non-Hodgkin lymphoma chemosensitive to salvage therapy with: (1) positron emission tomography-positive disease or (2) bone marrow involvement. Patients underwent standard HDT-ASCT followed by 19-28z CAR T cells on days +2 and +3. Of 15 subjects treated on study, dose-limiting toxicity was observed at both dose levels (5 × 10 6  and 1 × 10 7  19-28z CAR T per kilogram). Ten of 15 subjects experienced CAR T-cell-induced neurotoxicity and/or cytokine release syndrome (CRS), which were associated with greater CAR T-cell persistence ( P  = .05) but not peak CAR T-cell expansion. Serum interferon-γ elevation ( P  < .001) and possibly interleukin-10 ( P  = .07) were associated with toxicity. The 2-year progression-free survival (PFS) is 30% (95% confidence interval, 20% to 70%).  Subjects given decreased naive-like (CD45RA + CCR7 + ) CD4 +  and CD8 +  CAR T cells experienced superior PFS ( P  = .02 and .04, respectively). There was no association between CAR T-cell peak expansion, persistence, or cytokine changes and PFS. 19-28z CAR T cells following HDT-ASCT were associated with a high incidence of reversible neurotoxicity and CRS. Following HDT-ASCT, effector CD4 +  and CD8 +  immunophenotypes may improve disease control. This trial was registered at www.clinicaltrials.gov as #NCT01840566., (© 2019 by The American Society of Hematology.)

Background: Clinically validated prognostic models for overall survival do not exist for patients with relapsed or refractory chronic lymphocytic leukaemia (CLL) who are on targeted therapies. We aimed to create a prognostic model to identify high-risk individuals who do not achieve a good outcome with available targeted therapies., Methods: In this retrospective, pooled cohort study, 2475 patients with CLL treated between June 22, 2012, and Sept 23, 2015, in six randomised trials of ibrutinib, idelalisib, and venetoclax, or at the Mayo Clinic CLL Database (MCCD) were included. Eligible patients had CLL, were previously treated, were aged 18 years or older, had ECOG performance status 0-1, and required further treatment as per the international workshop on CLL 2008 criteria. There was heterogeneity in other eligibility criteria. We evaluated 28 candidate factors known to affect the overall survival of these patients and applied univariate and multivariate analyses to derive the risk score in a training dataset (n=727) of patients treated with ibrutinib or chemoimmunotherapy. We validated the score in an internal-validation dataset (n=242) of patients treated with ibrutinib or chemoimmunotherapy and three external-validation datasets (idelalisib or chemoimmunotherapy dataset, n=897; venetoclax or chemoimmunotherapy dataset, n=389; and the MCCD [including patients treated with heterogeneous therapies], n=220), applying C-statistics as a measure of discrimination., Findings: The derived model consisted of four factors (one point each; serum β 2 -microglobulin ≥5 mg/dL, lactate dehydrogenase >upper limit of normal, haemoglobin <110 g/L for women or <120 g/L for men, and time from initiation of last therapy <24 months), separating patients into low (score 0-1), intermediate (score 2-3), and high risk (score 4) groups. The risk score was prognostic for overall survival in the training dataset (CS=0·74, 95% CI 0·60-0·85, log-rank p<0·0001), and in the internal-validation (CS=0·79, 0·56-0·97, log-rank p=0·0003), and all three external-validation cohorts (idelalisib or chemoimmunotherapy: CS=0·71, 0·59-0·81, log-rank p<0·0001; venetoclax or chemoimmunotherapy: CS =0·76, 0·66-0·85, log-rank p=0·014; MCCD cohort: CS=0·61, 0·56-0·66), log-rank p<0·0001). The risk score is available on Calculate by QxMD., Interpretation: We present the first validated risk score to predict overall survival in patients with relapsed or refractory CLL treated with targeted therapy. The model is applicable to patients treated with all currently approved targeted therapies (ibrutinib, idelalisib, and venetoclax) and chemoimmunotherapy. This tool allows the identification of a well defined cohort of previously treated patients with CLL who are at high risk of death, and could be used in future prospective trials to test therapeutic options for these patients with an unmet clinical need., Funding: Lymphoma Research Foundation, Lymphoma Research Fund (Andrew D Zelenetz), and National Institutes of Health/National Cancer Institute., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The spectrum and evolution of proliferation rates in stage IV lung carcinoids is poorly defined. In particular, there are limited data on the prevalence and characteristics of tumors exceeding the standard upper proliferative criteria-as defined largely based on early-stage carcinoids-in metastatic setting. Sixty-six patients with stage IV lung carcinoids were identified, and all evaluable samples (n = 132; mean 2 samples per patient) were analyzed for mitotic counts and Ki-67 rate. Clinicopathologic and genomic features associated with elevated proliferation rates (>10 mitoses per 2 mm 2 and/or >20% hot-spot Ki-67), and evolution of proliferation rates in serial specimens were analyzed. We found that mitoses and/or Ki-67 exceeded the standard criteria in 35 of 132 (27%) samples, primarily (31/35 cases) at  metastatic sites. Although neuroendocrine neoplasms with >10 mitoses per 2 mm 2 are currently regarded as de facto neuroendocrine carcinomas, the notion that these cases are part of the spectrum of carcinoids was supported by (1) well-differentiated morphology, (2) conventional proliferation rates in other samples from same patient, (3) genetic characteristics, including the lack of RB1/TP53 alterations in all tested samples (n = 19), and (4) median overall survival of 2.7 years, compared to <1 year survival of stage IV neuroendocrine carcinomas in the historic cohorts. In patients with matched primary/metastatic specimens (48 pairs), escalation of mitoses or Ki-67 by ≥10 points was observed in 35% of metastatic samples; clonal relationship in one pair with marked proliferative progression was confirmed by next-generation sequencing. Notably, escalation of proliferation rate was documented in a subset of metastases arising from resected typical carcinoids, emphasizing that the diagnosis of typical carcinoid in primary tumor does not assure low proliferation rate at metastatic sites. In conclusion, stage IV lung carcinoids frequently exceed the standard proliferative criteria established for primary tumors, and commonly exhibit proliferative escalation at metastatic sites. Despite the overlap of proliferation rates, these tumors show fundamental morphologic, genomic and clinical differences from neuroendocrine carcinomas, and should be classified separately from those tumors. Awareness of the increased proliferative spectrum in metastatic carcinoids is critical for their accurate diagnosis. Further studies are warranted to explore the impact of proliferation indices on prognosis and therapeutic responses of patients with metastatic carcinoids.

The CLL-IPI is a risk-weighted prognostic model for previously untreated patients with chronic lymphocytic leukemia (CLL), but has not been evaluated in patients with relapsed CLL or on novel therapies. We evaluated the CLL-IPI in 897 patients with relapsed/refractory CLL in 3 randomized trials testing idelalisib (PI3Kδ inhibitor). The CLL-IPI identified patients as low (2.2%), intermediate (12.8%), high (48.7%), and very high (36.2%) risk and was prognostic for survival (log-rank p  < .0001; C-statistic 0.706). Of CLL-IPI factors, age >65, β2-microglobulin >3.5mg/L, unmutated immunoglobulin heavy chain variable region gene, and deletion 17p/ TP53 mutation were independently prognostic, but Rai I-IV or Binet B/C was not. The CLL-IPI is prognostic for survival in relapsed CLL and with idelalisib therapy. However, low/intermediate risk is uncommon, and regression parameters of individual factors in this risk-weighted model appear different in relapsed CLL. Reassessment of the weighting of the individual variables might optimize the model in this setting.

KRAS G12D-mutant/p53-deficient non-small-cell lung cancer (NSCLC) models are dependent on the NF-κB pathway that can be down-regulated by the proteasome inhibitor bortezomib. Two exceptional responders were observed on prior clinical trials of bortezomib, both of whom had KRAS G12D-mutant NSCLC, prompting the initiation of this single-center phase 2 trial. Patients with advanced KRAS G12D-mutant NSCLC were eligible. Bortezomib was administered at 1.3 mg/m 2 subcutaneously (days 1, 4, 8, 11; 21-d cycle) until progression or unacceptable toxicity. The primary objective was best objective response (RECIST v1.1). Sixteen patients with KRAS G12D-mutant lung adenocarcinomas were treated. Patients had a median pack year smoking history of 4 (range 0-45). A partial response (PR) was observed in one patient (-66% from baseline) and stable disease in five patients on the first stage of this study (overall response rate of 6%, 95% CI: 0.2-30.2), and further patients were not accrued. The median progression-free survival was 1 mo (95% CI: 1-6). The median overall survival was 13 mo (95% CI: 6-NA). The most common treatment-related adverse events were fatigue (38%) and diarrhea (26%). TP53 status did not predict response on exploratory testing. Of note, the patient with a PR had a unique subtype of lung adenocarcinoma-invasive mucinous adenocarcinomas (IMA)-and had rapid clinical improvement and substantial disease regression, which was also previously observed in two other patients with advanced KRAS G12D-mutant lung cancer with IMAs who received bortezomib on separate clinical trials. Exceptional responses to bortezomib can be achieved in KRAS G12D-mutant NSCLCs. KRAS G12D mutation alone, however, is not a robust predictor of response. Further evaluation should only be performed after further elucidation of other factors such as co-occurring alterations and histologic subtype such as IMA that may predict sensitivity to therapy., (© 2019 Drilon et al.; Published by Cold Spring Harbor Laboratory Press.)

Purpose: Ipilimumab induces durable remission in about 15-20% of patients with metastatic melanoma. However, reliable predictors of response to ipilimumab are currently lacking. Whole-body metabolic tumor volume (wMTV) has been shown to be a strong prognostic factor in a variety of malignancies treated with chemotherapy, but few results have been reported for patients treated with immunotherapy. The purpose of this study was to investigate the prognostic value of wMTV and other metabolic parameters from baseline 18 F-FDG PET/CT scans in patients with melanoma being treated with ipilimumab., Methods: The prognostic impact of wMTV, as well as mean standardized uptake values and total lesion glycolysis, was evaluated in 142 consecutive patients with melanoma treated with single-agent ipilimumab therapy. Metabolic parameters were dichotomized by their respective medians and correlated with overall survival (OS). In addition, the prognostic value of metabolic parameters combined with known clinical prognostic factors was evaluated in multivariate analyses., Results: The median OS time in all patients was 14.7 months (95% CI 10.45-18.93 months). wMTV was a strong independent prognostic factor for OS (p = 0.001). The median survival in patients with a metabolic volume above the median was 10.8 months (95% CI 5.88-15.81 months) as compared with 26.0 months (95% CI 3.02-49.15 months) in patients with an MTV below the median. A multivariate model including wMTV and known clinical prognostic factors, such as age and the presence of brain metastases, further improved the identification of patient subgroups with different OS times., Conclusion: wMTV appears to be a strong independent prognostic factor in melanoma patients treated with ipilimumab, and can be determined semiautomatically from routine 18 F- FDG PET/CT scans. wMTV, combined with clinical prognostic factors, could be used to personalize immunotherapy and in future clinical studies.

Immune checkpoint inhibitors (ICIs) are now commonly used to treat patients with metastatic malignant melanoma. Although concerns have been raised that the inflammatory response induced by ICIs may limit the ability of 18 F-FDG PET/CT to assess tumor response, systematic analyses on the use of 18 F-FDG PET/CT in this setting are mostly lacking. Thus, we set out to evaluate the association between tumor response on 18 F-FDG PET/CT and prognosis in patients with metastatic malignant melanoma treated with ipilimumab. Methods: We analyzed 60 consecutive patients with metastatic melanoma who underwent 18 F-FDG PET/CT scans both before and after treatment to evaluate treatment response after completion of ipilimumab therapy. Tumor response was assessed by the change in the sum of SULpeak (voxels with the highest average SUL [SUV normalized to lean body mass]) of up to 5 lesions according to PERCIST5. New lesions on PET that appeared suggestive of metastases were considered progressive metabolic disease (PMD). Because immunotherapy may cause new inflammatory lesions that are detectable on 18 F-FDG PET/CT, we also evaluated an immunotherapy-modified response classification (imPERCIST5). In this classification, new lesions do not define PMD per se; rather, PMD requires an increase in the sum of SULpeak by 30%. The correlation between tumor response according to these 3 definitions and overall survival (OS) was evaluated and compared with known prognostic factors. Results: In responders and nonresponders, the 2-y OS was 66% versus 29% for imPERCIST5 ( P = 0.003). After multivariate analysis, imPERCIST5 remained prognostic (hazard ratio, 3.853; 95% confidence interval, 1.498-9.911; P = 0.005). New sites of focal 18 F-FDG uptake occurred more often in patients with PMD ( n = 24) by imPERCIST5 than in those with stable metabolic disease ( n = 7) or partial metabolic response ( n = 4). In patients with partial metabolic response, 2 of 4 isolated new lesions regressed spontaneously during follow-up. Conclusion: In patients with metastatic melanoma treated with ipilimumab, tumor response according to PERCIST was associated with OS. Our data suggest that PMD should not be defined by the appearance of new lesions, but rather by an increase in the sum of SULpeak., (© 2019 by the Society of Nuclear Medicine and Molecular Imaging.)

Background and Aims: There is considerable interest in epidemiology to estimate an additive interaction effect between two risk factors in case-control studies. An additive interaction is defined as the differential reduction in absolute risk associated with one factor between different levels of the other factor. A stratified two-phase case-control design is commonly used in epidemiology to reduce the cost of assembling covariates. It is crucial to obtain valid estimates of the model parameters by accounting for the underlying stratification scheme to obtain accurate and precise estimates of additive interaction effects. The aim of this paper is to examine the properties of different methods for estimating model parameters and additive interaction effects under a stratified two-phase case-control design., Methods: Using simulations, we investigate the properties of three existing methods, namely stratum-specific offset, inverse-probability weighting, and multiple imputation for estimating model parameters and additive interaction effects. We also illustrate these properties using data from two published epidemiology studies., Results: Simulation studies show that the multiple imputation method performs well when both the true and analysis models are additive (i.e., does not include multiplicative interaction terms) but does not provide a discernible advantage over the offset method when the analysis models are non-additive (i.e., includes multiplicative interaction terms). The offset method exhibits the best overall properties when the analysis model contains multiplicative interaction effects., Conclusion: When estimating additive interaction between risk factors in stratified two-phase case-control studies, we recommend estimating model parameters using multiple imputation when the analysis model is additive, and we recommend the offset method when the analysis model is non-additive., (© 2019 S. Karger AG, Basel.)

Regularized variable selection is a powerful tool for identifying the true regression model from a large number of candidates by applying penalties to the objective functions. The penalty functions typically involve a tuning parameter that control the complexity of the selected model. The ability of the regularized variable selection methods to identify the true model critically depends on the correct choice of the tuning parameter. In this study we develop a consistent tuning parameter selection method for regularized Cox's proportional hazards model with a diverging number of parameters. The tuning parameter is selected by minimizing the generalized information criterion. We prove that, for any penalty that possesses the oracle property, the proposed tuning parameter selection method identifies the true model with probability approaching one as sample size increases. Its finite sample performance is evaluated by simulations. Its practical use is demonstrated in the Cancer Genome Atlas (TCGA) breast cancer data.

Case-cohort designs are commonly used in large epidemiological studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large. An efficient variable selection method is needed for case-cohort studies where the covariates are only observed in a subset of the sample. Current literature on this topic has been focused on the proportional hazards model. However, in many studies the additive hazards model is preferred over the proportional hazards model either because the proportional hazards assumption is violated or the additive hazards model provides more relevent information to the research question. Motivated by one such study, the Atherosclerosis Risk in Communities (ARIC) study, we investigate the properties of a regularized variable selection procedure in stratified case-cohort design under an additive hazards model with a diverging number of parameters. We establish the consistency and asymptotic normality of the penalized estimator and prove its oracle property. Simulation studies are conducted to assess the finite sample performance of the proposed method with a modified cross-validation tuning parameter selection methods. We apply the variable selection procedure to the ARIC study to demonstrate its practical use.

Purpose: KRAS mutations occur in approximately 25% of patients with non-small cell lung cancer (NSCLC). Despite the uniform presence of KRAS mutations, patients with KRAS -mutant NSCLC can have a heterogeneous clinical course. As the pattern of co-occurring mutations may describe different biological subsets of patients with KRAS -mutant lung adenocarcinoma, we explored the effects of co-occurring mutations on patient outcomes and response to therapy. Experimental Design: We identified patients with advanced KRAS -mutant NSCLC and evaluated the most common co-occurring genomic alterations. Multivariate analyses were performed incorporating the most frequent co-mutations and clinical characteristics to evaluate association with overall survival as well as response to platinum-pemetrexed chemotherapy and immune checkpoint inhibitors. Results: Among 330 patients with advanced KRAS -mutant lung cancers, the most frequent co-mutations were found in TP53 (42%), STK11 (29%), and KEAP1 / NFE2L2 (27%). In a multivariate analysis, there was a significantly shorter survival in patients with co-mutations in KEAP1 / NFE2L2 [HR, 1.96; 95% confidence interval (CI), 1.33-2.92; P ≤ 0.001]. STK11 (HR, 1.3; P = 0.22) and TP53 (HR 1.11, P = 0.58) co-mutation statuses were not associated with survival. Co-mutation in KEAP1 / NFE2L2 was also associated with shorter duration of initial chemotherapy (HR, 1.64; 95% CI, 1.04-2.59; P = 0.03) and shorter overall survival from initiation of immune therapy (HR, 3.54; 95% CI, 1.55-8.11; P = 0.003). Conclusions: Among people with KRAS -mutant advanced NSCLC, TP53, STK11 , and KEAP1 / NFE2L2 are the most commonly co-occurring somatic genomic alterations. Co-mutation of KRAS and KEAP1 / NFE2L2 is an independent prognostic factor, predicting shorter survival, duration of response to initial platinum-based chemotherapy, and survival from the start of immune therapy. Clin Cancer Res; 24(2); 334-40. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Case-cohort designs are widely used in large cohort studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large, so an efficient variable selection method is necessary. In this paper, we study the properties of a variable selection procedure using the smoothly clipped absolute deviation penalty in a case-cohort design with a diverging number of parameters. We establish the consistency and asymptotic normality of the maximum penalized pseudo-partial-likelihood estimator, and show that the proposed variable selection method is consistent and has an asymptotic oracle property. Simulation studies compare the finite-sample performance of the procedure with tuning parameter selection methods based on the Akaike information criterion and the Bayesian information criterion. We make recommendations for use of the proposed procedures in case-cohort studies, and apply them to the Busselton Health Study.

Pulmonary fibrosis, the end stage of a variety of fibroproliferative lung diseases, is usually induced after repetitive or chronic lung injury or inflammation. The mechanisms of fibroproliferation are poorly understood. Insulin-like growth factor-I (IGF-I) is significantly elevated in patients with pulmonary fibrosis and fibroproliferative acute respiratory distress syndrome. However, we showed that IGF-I overexpression alone in wild-type mouse lungs does not cause fibroproliferation. We therefore questioned whether IGF-I, acting together with active TGF-β1, a known profibrotic cytokine, enhances pulmonary fibroproliferation caused by active TGF-β1. A unique sequential adenoviral transgene mouse model was used expressing AdEmpty/AdTGF-β1 or AdhIGF-IB/AdTGF-β1 transgenes. IGF-IB plus active TGF-β1 transgene expression synergistically increased collagen deposition in the lung parenchyma compared with active TGF-β1 expression alone. The enhanced fibrosis was accompanied by an increased recruitment of macrophages and lymphocytes into the bronchoalveolar lavage fluid (BALF) and inflammatory cells in the lungs. α-Smooth muscle actin expression, a marker of myofibroblast proliferation and differentiation, was also increased. Finally, fibroblasts exposed ex vivo to BALF isolated from AdhIGF-IB/AdTGF-β1-transduced mice showed synergistic collagen induction compared with BALF from AdEmpty/AdTGF-β1-transduced mice. This study provides the first direct evidence that IGF-I is able to synergistically enhance pulmonary fibroproliferation in cooperation with TGF-β1.

Pulmonary fibrosis (PF), the end stage of a variety of fibroproliferative lung diseases, is characterized by excessive lung mesenchymal cell activation and extracellular matrix deposition. Most PF is induced after repetitive or chronic lung inflammation; however, a significant portion of PF occurs without apparent inflammation. The mechanisms of fibroproliferation are poorly understood. Studies have shown that cytokines regulating inflammation and tissue repair processes play essential roles in the development of PF. Insulin-like growth factor I (IGF-I) has been shown to stimulate lung mesenchymal cell proliferation and extracellular matrix synthesis in vitro and is significantly elevated in patients with PF. In this study, we investigated whether human IGF-IB (hIGF-IB) expression in the lungs induces PF in a C57BL/6 mouse model. Mice were subjected to adenoviral gene transfer, and the effects of hIGF-IB expression on the lungs were examined 3, 7, 14, 21, and 42 days after gene delivery. hIGF-IB expression induced significant and prolonged inflammatory cell infiltration into the lungs, with an early neutrophil infiltration followed by a late macrophage infiltration. No significant fibroblast or matrix accumulation could be detected in the lungs of these mice. No significant collagen accumulation could be detected in vivo, despite in vitro evidence that hIGF-IB induces collagen mRNA expression in fibroblasts. Therefore, IGF-IB alone is not sufficient to induce fibrosis, and it is possible that a coactivator is required to induce significant fibroproliferation in vivo.