Introduction We are conducting a multicenter study to identify classifiers predictive of disease-specific survival in patients with primary melanomas. Here we delineate the unique aspects, challenges, and best practices for optimizing a study of generally small-sized pigmented tumor samples including primary melanomas of at least 1.05mm from AJTCC TNM stage IIA-IIID patients. We also evaluated tissue-derived predictors of extracted nucleic acids’ quality and success in downstream testing. This ongoing study will target 1,000 melanomas within the international InterMEL consortium. Methods Following a pre-established protocol, participating centers ship formalin-fixed paraffin embedded (FFPE) tissue sections to Memorial Sloan Kettering Cancer Center for the centralized handling, dermatopathology review and histology-guided coextraction of RNA and DNA. Samples are distributed for evaluation of somatic mutations using next gen sequencing (NGS) with the MSK-IMPACT TM assay, methylation-profiling (Infinium MethylationEPIC arrays), and miRNA expression (Nanostring nCounter Human v3 miRNA Expression Assay). Results Sufficient material was obtained for screening of miRNA expression in 683/685 (99%) eligible melanomas, methylation in 467 (68%), and somatic mutations in 560 (82%). In 446/685 (65%) cases, aliquots of RNA/DNA were sufficient for testing with all three platforms. Among samples evaluated by the time of this analysis, the mean NGS coverage was 249x, 59 (18.6%) samples had coverage below 100x, and 41/414 (10%) failed methylation QC due to low intensity probes or insufficient Meta-Mixed Interquartile (BMIQ)- and single sample (ss)- Noob normalizations. Six of 683 RNAs (1%) failed Nanostring QC due to the low proportion of probes above the minimum threshold. Age of the FFPE tissue blocks (p<0.001) and time elapsed from sectioning to co-extraction (p = 0.002) were associated with methylation screening failures. Melanin reduced the ability to amplify fragments of 200bp or greater (absent/lightly pigmented vs heavily pigmented, p<0.003). Conversely, heavily pigmented tumors rendered greater amounts of RNA (p<0.001), and of RNA above 200 nucleotides (p<0.001). Conclusion Our experience with many archival tissues demonstrates that with careful management of tissue processing and quality control it is possible to conduct multi-omic studies in a complex multi-institutional setting for investigations involving minute quantities of FFPE tumors, as in studies of early-stage melanoma. The study describes, for the first time, the optimal strategy for obtaining archival and limited tumor tissue, the characteristics of the nucleic acids co-extracted from a unique cell lysate, and success rate in downstream applications. In addition, our findings provide an estimate of the anticipated attrition that will guide other large multicenter research and consortia.
Patients with stage II and III cutaneous primary melanoma vary considerably in their risk of melanoma-related death. We explore the ability of methylation profiling to distinguish primary melanoma methylation classes and their associations with clinicopathologic characteristics and survival.
Introduction: Decreased brain-derived neurotrophic factor (BDNF) is associated with poor sleep. This study examined the effects of acupuncture versus cognitive behavioral therapy for insomnia (CBT-I) on serum BDNF and sleep outcomes in cancer survivors with insomnia. Methods: This was an exploratory analysis of a randomized clinical trial (n = 160) comparing acupuncture versus CBT-I for cancer survivors with insomnia. Interventions were delivered over 8 weeks. Outcomes were assessed at baseline and week 8. Serum BDNF was evaluated with enzyme-linked immunosorbent assay (ELISA). Sleep was evaluated with the insomnia severity index and consensus sleep diary. Pearson correlations between BDNF and sleep outcomes were calculated. Data analysis was limited to 87 survivors who provided serum samples. Results: Among 87 survivors, the mean age was 61.9 (SD: 11.4) years, 51.7% were women, and 24.1% were non-White. Mean serum BDNF did not significantly increase in acupuncture (n = 50) or CBT-I (n = 37) groups. When analysis was restricted to patients with low baseline BDNF (i.e. levels below the sample median of 47.1 ng/mL), the acupuncture group (n = 22) demonstrated a significant 7.2 ng/mL increase in mean serum BDNF (P = 0.03), whereas the CBT-I group (n = 21) demonstrated a non-significant 2.9 ng/mL increase (P = 0.28). Serum BDNF was not significantly correlated with sleep outcomes (all P > 0.05). Conclusion: Among cancer survivors with insomnia and low baseline BDNF, acupuncture significantly increased serum BDNF levels; however, the clinical significance of this finding requires further investigation. Trial registration no. NCT02356575 (ClinicalTrials.gov)
Abstract Identifying predictive biomarkers of patient outcomes from high-throughput microbiome data is of high interest, while existing computational methods do not satisfactorily account for complex survival endpoints, longitudinal samples, and taxa-specific sequencing biases. We present FLORAL ( https://vdblab.github.io/FLORAL/ ), an open-source computational tool to perform scalable log-ratio lasso regression and microbial feature selection for continuous, binary, time-to-event, and competing risk outcomes, with compatibility of longitudinal microbiome data as time-dependent covariates. The proposed method adapts the augmented Lagrangian algorithm for a zero-sum constraint optimization problem while enabling a two-stage screening process for extended false-positive control. In extensive simulation and real-data analyses, FLORAL achieved consistently better false-positive control compared to other lasso-based approaches, and better sensitivity over popular differential abundance testing methods for datasets with smaller sample size. In a survival analysis in allogeneic hematopoietic-cell transplant, we further demonstrated considerable improvement by FLORAL in microbial feature selection by utilizing longitudinal microbiome data over only using baseline microbiome data.
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