Quantitative Assessment of Tissue Biomarkers and Construction of a Model to Predict Outcome in Breast Cancer Using Multiple Imputation

Missing data pose one of the greatest challenges in the rigorous evaluation of biomarkers. The limited availability of specimens with complete clinical annotation and quality biomaterial often leads to underpowered studies. Tissue microarray studies, for example, may be further handicapped by the loss of data points because of unevaluable staining, core loss, or the lack of tumor in the histospot. This paper presents a novel approach to these common problems in the context of a tissue protein biomarker analysis in a cohort of patients with breast cancer. Our analysis develops techniques based on multiple imputation to address the missing value problem. We first select markers using a training cohort, identifying a small subset of protein expression levels that are most useful in predicting patient survival. The best model is obtained by including both protein markers (including COX6C, GATA3, NAT1, and ESR1) and lymph node status. The use of either lymph node status or the four protein expression levels provides similar improvements in goodness-of-fit, with both significantly better than a baseline clinical model. Using the same multiple imputation strategy, we then validate the results out-of-sample on a larger independent cohort. Our approach of integrating multiple imputation with each stage of the analysis serves as an example that may be replicated or adapted in future studies with missing values

Metatranscriptome of human faecal microbial communities in a cohort of adult men

The gut microbiome is intimately related to human health, but it is not yet known which functional activities are driven by specific microorganisms\u27 ecological configurations or transcription. We report a large-scale investigation of 372 human faecal metatranscriptomes and 929 metagenomes from a subset of 308 men in the Health Professionals Follow-Up Study. We identified a metatranscriptomic \u27core\u27 universally transcribed over time and across participants, often by different microorganisms. In contrast to the housekeeping functions enriched in this core, a \u27variable\u27 metatranscriptome included specialized pathways that were differentially expressed both across participants and among microorganisms. Finally, longitudinal metagenomic profiles allowed ecological interaction network reconstruction, which remained stable over the six-month timespan, as did strain tracking within and between participants. These results provide an initial characterization of human faecal microbial ecology into core, subject-specific, microorganism-specific and temporally variable transcription, and they differentiate metagenomically versus metatranscriptomically informative aspects of the human faecal microbiome

Stability of the human faecal microbiome in a cohort of adult men

Characterizing the stability of the gut microbiome is important to exploit it as a therapeutic target and diagnostic biomarker. We metagenomically and metatranscriptomically sequenced the faecal microbiomes of 308 participants in the Health Professionals Follow-Up Study. Participants provided four stool samples—one pair collected 24–72 h apart and a second pair ~6 months later. Within-person taxonomic and functional variation was consistently lower than between-person variation over time. In contrast, metatranscriptomic profiles were comparably variable within and between subjects due to higher within-subject longitudinal variation. Metagenomic instability accounted for ~74% of corresponding metatranscriptomic instability. The rest was probably attributable to sources such as regulation. Among the pathways that were differentially regulated, most were consistently over- or under-transcribed at each time point. Together, these results suggest that a single measurement of the faecal microbiome can provide long-term information regarding organismal composition and functional potential, but repeated or short-term measures may be necessary for dynamic features identified by metatranscriptomics

Application of a lifestyle-based score to predict cardiovascular risk in African Americans: The Jackson heart study

Cardiovascular disease (CVD) primordial prevention tools applicable to diverse popula-tions are scarce. Our aim was to assess the performance of a lifestyle-based tool to estimate CVD risk in an African American population. The Jackson Heart Study is a prospective cohort including 5306 African American participants in Jackson, Mississippi (2000–2004), with a mean follow up of 12 years. The Healthy Heart Score is a lifestyle-based CVD risk prediction model based on nine components: body mass index (BMI), physical activity, smoking, and a 5-component diet score. Gender-specific beta coefficients from its derivation cohorts were used to assess the performance of the Healthy Heart Score. Model discrimination was assessed using Harrell’s C-Index for survival data and time dependent Area Under the Curve. Model calibration was evaluated through calibration plots. A total of 189 CVD events occurred. The Healthy Heart Score showed high-moderate discrimination for CVD events (C-statistic 0.75 [95% CI, 0.71–0.78]) but with little improvement over the age-only model. Both the age-only and Healthy Heart Score models had better performance in participants without diabetes at baseline and showed good calibration. In African Americans, the Healthy Heart Score does not improve prediction of mid-life CVD events beyond what is obtained by age alone.This research was funded by the National Heart, Lung, and Blood Institute, and the National Institute on Minority Health and Health Disparities, contract numbers HHSN268201300046C, HHSN268201300047C, HHSN268201300048C, HHSN268201300049C, HHSN268201300050C. M.S.-P. holds a Ramón y Cajal contract (RYC-2018-025069-I) from the Ministry of Science, Innovation and Universities and FEDER/FSE and a FIS grant PI20/00896 (Instituto de Salud Carlos III, State Secretary of R+D+I and FEDER/FSE). Preparation of this manuscript was supported by The Robert Wood Johnson Foundation (Harold Amos Medical Faculty Development Program ID# 76236, J.J.J.) and the National Institute of Diabetes and Digestive and Kidney Diseases (K23DK117041, J.J.J.) of the National Institutes of Healt

Reanalysis of the NCCN PD-L1 Companion Diagnostic Assay Study for Lung Cancer in the Context of PD-L1 Expression Findings in Triple-Negative Breast Cancer

The companion diagnostic test for checkpoint inhibitor immune therapy is an immunohistochemical test for PD-L1. The test has been shown to be reproducible for expression in tumor cells, but not in immune cells. Immune cells were used in the IMpassion130 trial which showed PD-L1 expression was associated with a better outcome. Two large studies have been done assessing immune cell PD-L1 expression in lung cancer. Here, we reanalyze one of those studies, to show that, even with an easier scoring method, there is still only poor agreement between assays and pathologist for immune cell PD-L1 expression

Expression of Drug Targets in Patients Treated with Sorafenib, Carboplatin and Paclitaxel

Introduction: Sorafenib, a multitarget kinase inhibitor, targets members of the mitogen-activated protein kinase (MAPK) pathway and VEGFR kinases. Here we assessed the association between expression of sorafenib targets and biomarkers of taxane sensitivity and response to therapy in pre-treatment tumors from patients enrolled in ECOG 2603, a phase III comparing sorafenib, carboplatin and paclitaxel (SCP) to carboplatin, paclitaxel and placebo (CP). Methods: Using a method of automated quantitative analysis (AQUA) of in situ protein expression, we quantified expression of VEGF-R2, VEGF-R1, VEGF-R3, FGF-R1, PDGF-Rβ, c-Kit, B-Raf, C-Raf, MEK1, ERK1/2, STMN1, MAP2, EB1 and Bcl-2 in pretreatment specimens from 263 patients. Results: An association was found between high FGF-R1 and VEGF-R1 and increased progression-free survival (PFS) and overall survival (OS) in our combined cohort (SCP and CP arms). Expression of FGF-R1 and VEGF-R1 was higher in patients who responded to therapy ((CR+PR) vs. (SD+PD+ un-evaluable)). Conclusions: In light of the absence of treatment effect associated with sorafenib, the association found between FGF-R1 and VEGF-R1 expression and OS, PFS and response might reflect a predictive biomarker signature for carboplatin/paclitaxel-based therapy. Seeing that carboplatin and pacitaxel are now widely used for this disease, corroboration in another cohort might enable us to improve the therapeutic ratio of this regimen. © 2013 Jilaveanu et al

Regulation of Glutamine Carrier Proteins by RNF5 Determines Breast Cancer Response to ER Stress-Inducing Chemotherapies

SummaryMany tumor cells are fueled by altered metabolism and increased glutamine (Gln) dependence. We identify regulation of the L-glutamine carrier proteins SLC1A5 and SLC38A2 (SLC1A5/38A2) by the ubiquitin ligase RNF5. Paclitaxel-induced ER stress to breast cancer (BCa) cells promotes RNF5 association, ubiquitination, and degradation of SLC1A5/38A2. This decreases Gln uptake, levels of TCA cycle components, mTOR signaling, and proliferation while increasing autophagy and cell death. Rnf5-deficient MMTV-PyMT mammary tumors were less differentiated and showed elevated SLC1A5 expression. Whereas RNF5 depletion in MDA-MB-231 cells promoted tumorigenesis and abolished paclitaxel responsiveness, SLC1A5/38A2 knockdown elicited opposing effects. Inverse RNF5hi/SLC1A5/38A2lo expression was associated with positive prognosis in BCa. Thus, RNF5 control of Gln uptake underlies BCa response to chemotherapies

Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome.

Despite known histological, biological, and clinical differences between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), relatively little is known about the spatial differences in their corresponding immune contextures. Our study of over 1000 LUAD and LUSC tumors revealed that computationally derived patterns of tumor-infiltrating lymphocytes (TILs) on H&E images were different between LUAD (N = 421) and LUSC (N = 438), with TIL density being prognostic of overall survival in LUAD and spatial arrangement being more prognostically relevant in LUSC. In addition, the LUAD-specific TIL signature was associated with OS in an external validation set of 100 NSCLC treated with more than six different neoadjuvant chemotherapy regimens, and predictive of response to therapy in the clinical trial CA209-057 (n = 303). In LUAD, the prognostic TIL signature was primarily comprised of CD4+ T and CD8+ T cells, whereas in LUSC, the immune patterns were comprised of CD4+ T, CD8+ T, and CD20+ B cells. In both subtypes, prognostic TIL features were associated with transcriptomics-derived immune scores and biological pathways implicated in immune recognition, response, and evasion. Our results suggest the need for histologic subtype-specific TIL-based models for stratifying survival risk and predicting response to therapy. Our findings suggest that predictive models for response to therapy will need to account for the unique morphologic and molecular immune patterns as a function of histologic subtype of NSCLC