Baseline correction for NMR spectroscopic metabolomics data analysis.

BackgroundWe propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of baseline distortion and constructs an optimal baseline curve to maximize it. The parameters are determined automatically by using LOWESS (locally weighted scatterplot smoothing) regression to estimate the noise variance.ResultsWe tested this method on 1D NMR spectra with different forms of baseline distortions, and demonstrated that it is effective for both regular 1D NMR spectra and metabolomics spectra with over-crowded peaks.ConclusionCompared with the automatic baseline correction function in XWINNMR 3.5, the penalized smoothing method provides more accurate baseline correction for high-signal density metabolomics spectra

Proteomic analyses reveal distinct chromatin-associated and soluble transcription factor complexes.

The current knowledge on how transcription factors (TFs), the ultimate targets and executors of cellular signalling pathways, are regulated by protein-protein interactions remains limited. Here, we performed proteomics analyses of soluble and chromatin-associated complexes of 56 TFs, including the targets of many signalling pathways involved in development and cancer, and 37 members of the Forkhead box (FOX) TF family. Using tandem affinity purification followed by mass spectrometry (TAP/MS), we performed 214 purifications and identified 2,156 high-confident protein-protein interactions. We found that most TFs form very distinct protein complexes on and off chromatin. Using this data set, we categorized the transcription-related or unrelated regulators for general or specific TFs. Our study offers a valuable resource of protein-protein interaction networks for a large number of TFs and underscores the general principle that TFs form distinct location-specific protein complexes that are associated with the different regulation and diverse functions of these TFs

SIRT7 Links H3K18 Deacetylation to Maintenance of Oncogenic Transformation

Sirtuin proteins regulate diverse cellular pathways that influence genomic stability, metabolism, and ageing. SIRT7 is a mammalian sirtuin whose biochemical activity, molecular targets, and physiologic functions have been unclear. Here we show that SIRT7 is an NAD$^+$-dependent H3K18Ac (acetylated lysine 18 of histone H3) deacetylase that stabilizes the transformed state of cancer cells. Genome-wide binding studies reveal that SIRT7 binds to promoters of a specific set of gene targets, where it deacetylates H3K18Ac and promotes transcriptional repression. The spectrum of SIRT7 target genes is defined in part by its interaction with the cancer-associated ETS transcription factor ELK4, and comprises numerous genes with links to tumour suppression. Notably, selective hypoacetylation of H3K18Ac has been linked to oncogenic transformation, and in patients is associated with aggressive tumour phenotypes and poor prognosis. We find that deacetylation of H3K18Ac by SIRT7 is necessary for maintaining essential features of human cancer cells, including anchorage-independent growth and escape from contact inhibition. Moreover, SIRT7 is necessary for a global hypoacetylation of H3K18Ac associated with cellular transformation by the viral oncoprotein E1A. Finally, SIRT7 depletion markedly reduces the tumourigenicity of human cancer cell xenografts in mice. Together, our work establishes SIRT7 as a highly selective H3K18Ac deacetylase and demonstrates a pivotal role for SIRT7 in chromatin regulation, cellular transformation programs, and tumour formation in vivo

Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications.

Analysis of DNA methylation patterns relies increasingly on sequencing-based profiling methods. The four most frequently used sequencing-based technologies are the bisulfite-based methods MethylC-seq and reduced representation bisulfite sequencing (RRBS), and the enrichment-based techniques methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylated DNA binding domain sequencing (MBD-seq). We applied all four methods to biological replicates of human embryonic stem cells to assess their genome-wide CpG coverage, resolution, cost, concordance and the influence of CpG density and genomic context. The methylation levels assessed by the two bisulfite methods were concordant (their difference did not exceed a given threshold) for 82% for CpGs and 99% of the non-CpG cytosines. Using binary methylation calls, the two enrichment methods were 99% concordant and regions assessed by all four methods were 97% concordant. We combined MeDIP-seq with methylation-sensitive restriction enzyme (MRE-seq) sequencing for comprehensive methylome coverage at lower cost. This, along with RNA-seq and ChIP-seq of the ES cells enabled us to detect regions with allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression

DNA damage response signatures are associated with frontline chemotherapy response and routes of tumor evolution in extensive stage small cell lung cancer

DNA damage; Frontline chemotherapy; Small cell lung cancerDaño del ADN; Quimioterapia de primera línea; Cáncer de pulmón de células pequeñasDany de l'ADN; Quimioteràpia de primera línia; Càncer de pulmó de cèl·lules petitesIntroduction A hallmark of small cell lung cancer (SCLC) is its recalcitrance to therapy. While most SCLCs respond to frontline therapy, resistance inevitably develops. Identifying phenotypes potentiating chemoresistance and immune evasion is a crucial unmet need. Previous reports have linked upregulation of the DNA damage response (DDR) machinery to chemoresistance and immune evasion across cancers. However, it is unknown if SCLCs exhibit distinct DDR phenotypes. Methods To study SCLC DDR phenotypes, we developed a new DDR gene analysis method and applied it to SCLC clinical samples, in vitro, and in vivo model systems. We then investigated how DDR regulation is associated with SCLC biology, chemotherapy response, and tumor evolution following therapy. Results Using multi-omic profiling, we demonstrate that SCLC tumors cluster into three DDR phenotypes with unique molecular features. Hallmarks of these DDR clusters include differential expression of DNA repair genes, increased replication stress, and heightened G2/M cell cycle arrest. SCLCs with elevated DDR phenotypes exhibit increased neuroendocrine features and decreased “inflamed” biomarkers, both within and across SCLC subtypes. Clinical analyses demonstrated treatment naive DDR status was associated with different responses to frontline chemotherapy. Using longitudinal liquid biopsies, we found that DDR Intermediate and High tumors exhibited subtype switching and coincident emergence of heterogenous phenotypes following frontline treatment. Conclusions We establish that SCLC can be classified into one of three distinct, clinically relevant DDR clusters. Our data demonstrates that DDR status plays a key role in shaping SCLC phenotypes and may be associated with different chemotherapy responses and patterns of tumor evolution. Future work targeting DDR specific phenotypes will be instrumental in improving patient outcomes.This work was supported by: NIH/NCI CCSG P30-CA016672 (MD Anderson Bioinformatics Shared Resource, and the MD Anderson Institutional Tissue bank (ITB)); The University of Texas-Southwestern and MD Anderson Cancer Center Lung SPORE P50-CA070907 (JW, JVH, CMG, LAB); NIH/NCI R01-CA207295 (LAB); NIH/NCI U01-CA213273 (JVH, LAB); NIH/NCI R50-CA243698 (CAS); NIH/NCI U01-CA256780 (JVH, LAB); NIH/NCI U24-CA213274 (LAB); The Department of Defense LC210510 (LAB); the LUNGevity Foundation 2020–02 (CMG); CPRIT RP210159 (CMG); Andrew Sabin Family Foundation (CMG); NETRF (CMG); NIH/NCI T32-CA009666 (KC); Rexanna’s Foundation for Fighting Lung Cancer (JVH, LAB, CMG); Jeffrey Lee Cousins Endowed Fellowship in Lung Cancer Research (BBM); and generous philanthropic contributions to The University of Texas MD Anderson Lung Cancer Moon Shot Program (JVH, CMG, LAB). BBM is a TRIUMPH Fellow in the CPRIT Research Training Program (RP210028). This research includes work performed in the Single Cell Genomics Core Facility, which is supported in part by CPRIT Single Core grant RP180684. LAB also acknowledges philanthropic support from A.R.K., L.W.Y., M.J.A., R.B.N., K.E.N., J.O., J.K.R., B. & B.N, C.K., P.C.B., S.S., S.R., and W.A.B

Noninvasive Genomic Profiling of Somatic Mutations in Oral Cavity Cancers

OBJECTIVES: Somatic mutations may predict prognosis, therapeutic response, or cancer progression. We evaluated targeted sequencing of oral rinse samples (ORS) for non-invasive mutational profiling of oral squamous cell carcinomas (OSCC). MATERIALS AND METHODS: A custom hybrid capture panel targeting 42 frequently mutated genes in OSCC was used to identify DNA sequence variants in matched ORS and fresh-frozen tumors from 120 newly-diagnosed patients. Receiver operating characteristic (ROC) curves determined the optimal variant allele fraction (VAF) cutoff for variant discrimination in ORS. Behavioral, clinical, and analytical factors were evaluated for impacts on assay performance. RESULTS: Half of tumors involved oral tongue (50 %), and a majority were T1-T2 tumor stage (55 %). Median depth of sequencing coverage was 260X for OSCC and 1,563X for ORS. Frequencies of single nucleotide variants (SNVs) at highly mutated genes (including TP53, FAT1, HRAS, NOTCH1, CDKN2A, CASP8, NFE2L2, and PIK3CA) in OSCC were highly correlated with TCGA data (R = 0.96, p = 2.5E-22). An ROC curve with area-under-the-curve (AUC) of 0.80 showed that, at an optimal VAF cutoff of 0.10 %, ORS provided 76 % sensitivity, 96 % specificity, but precision of only 2.6E-4. At this VAF cutoff, 206 of 270 SNVs in OSCC were detected in matched ORS. Sensitivity varied by patient, T stage and target gene. Neither downsampled ORS as matched control nor a naïve Bayesian classifier adjusting for sequencing bias appreciably improved assay performance. CONCLUSION: Targeted sequencing of ORS provides moderate assay performance for noninvasive detection of SNVs in OSCC. Our findings strongly rationalize further clinical and laboratory optimization of this assay, including strategies to improve precision

Transcriptomic, Proteomic, and Genomic Mutational Fraction Differences Based on HPV Status Observed in Patient-Derived Xenograft Models of Penile Squamous Cell Carcinoma

Simple Summary Penile cancer is a rare but aggressive cancer. After it metastasizes, the median survival time is less than 12 months. The overall response rate to common first-line combination chemotherapy treatments is approximately 50%. There is an urgent need in advanced-penile-cancer treatment to find novel therapies that would generate better response rates than standard chemotherapy thus far and have less toxicity. Partially due to its rarity, there are few animal models and cell lines of penile cancer. We report on the generation of seven penile cancer animal models that were created by directly implanting human tumor tissue into immunocompromised mice. Abstract Metastatic penile squamous cell carcinoma (PSCC) has only a 50% response rate to first-line combination chemotherapies and there are currently no targeted-therapy approaches. Therefore, we have an urgent need in advanced-PSCC treatment to find novel therapies. Approximately half of all PSCC cases are positive for high-risk human papillomavirus (HR-HPV). Our objective was to generate HPV-positive (HPV+) and HPV-negative (HPV−) patient-derived xenograft (PDX) models and to determine the biological differences between HPV+ and HPV− disease. We generated four HPV+ and three HPV− PSCC PDX animal models by directly implanting resected patient tumor tissue into immunocompromised mice. PDX tumor tissue was found to be similar to patient tumor tissue (donor tissue) by histology and short tandem repeat fingerprinting. DNA mutations were mostly preserved in PDX tissues and similar APOBEC (apolipoprotein B mRNA editing catalytic polypeptide) mutational fractions in donor tissue and PDX tissues were noted. A higher APOBEC mutational fraction was found in HPV+ versus HPV− PDX tissues (p = 0.044), and significant transcriptomic and proteomic expression differences based on HPV status included p16 (CDKN2A), RRM2, and CDC25C. These models will allow for the direct testing of targeted therapies in PSCC and determine their response in correlation to HPV status