Biology subjects

Khalil, S.

Publications and source records attributed to Khalil, S..

10 recordsLinked to original sources

bioRxiv2026

Tissue Memory Score measures transcriptional retention in solidtumors and predicts survival in clear cell renal cell carcinoma

Solid tumors retain transcriptional programs inherited from their tissue of origin, but the degree of this retention has not been quantified as a continuous metric, nor has its prognostic relevance been evaluated systematically. We developed the Tissue Memory Score (TMS) by projecting tumor bulk RNA-seq onto principal component axes constructed from 2,694 Genotype-Tissue Expression V8 samples across eight healthy tissues, and applied it to 3,900 primary tumors from eight Cancer Genome Atlas cohorts. Nearest-centroid classification recovered tissue identity in six of eight tumor types (80.1%-100.0% accuracy; chance 12.5%; all p < 10-). The two failures, gastric and endometrial carcinoma, reflected limitations of the reference atlas composition and not loss of tissue memory. Among cohorts passing pre-specified retention and dedifferentiation gates, TMS was independently associated with overall survival in clear cell renal cell carcinoma (ccRCC; multivariable HR = 0.59 per SD; 95% CI 0.46-0.77; p = 6.6 x 10-) and accounted for 16.3% of explained survival variance by Shapley decomposition. The association held under purity residualization, rank transformation, stage stratification, and progression-free interval as an alternative endpoint. In hepatocellular carcinoma, TMS showed a protective univariable association in the same direction, which did not survive multivariable adjustment and is reported as exploratory. External application to CPTAC-ccRCC yielded a pooled hazard ratio of 0.71 in the same direction (I{superscript 2} = 0%). Tissue-of-origin transcriptional memory is quantifiable in solid tumors and independently prognostic in ccRCC, but did not extend to the remaining seven cohorts. Broader applicability depends on whether the reference atlas represents the cellular compartment from which a given carcinoma arises.

cancer biology↗

bioRxiv2026

Prospective ICH Q2(R2)-aligned total-error validation of label-free untargeted proteomics for host cell protein quantification in biotherapeutics

Untargeted proteomics enables quantitative determination of host cell proteins (HCPs) in biotherapeutics, yet no workflow has been validated under ICH Q2(R2) for regulated quality control. We report a prospective validation of label-free untargeted proteomics for HCP quantification using a total-error (TE) approach. A stable isotope-labeled whole-proteome standard was spiked into NISTmAb at seven levels (20-80 ng). Four independent assays (198 injections) supported hierarchical replication and one-way random-effects ANOVA variance decomposition with Welch-Satterthwaite adjustment. Dual entrapment analysis demonstrated empirical peptide-level false discovery proportions below 1% at q = 0.01. Deterministic parsimony inference ensured invariant protein-group definition. Weighted least-squares regression (R{superscript 2} = 0.993) identified stable proportional compression with recoveries of 81-85%. Repeatability dominated the variance structure (median CV 2.7%); intermediate precision total SD ranged from 0.69% to 3.81% over the validated range. Accuracy profiles integrating empirical bias with a log- log variance model showed 95% {beta}-expectation and 95/95 content tolerance intervals fully contained within {+/-}30%, with a lower limit of quantification (LLOQ) of 20 ng. Abundance-stratified TE analysis revealed concentration-dependent calibration heterogeneity masked by aggregate-level estimation; stratum-specific {beta}-expectation intervals within {+/-}35% defined an abundance-aware LLOQ of 3.6 ppm (P95 = 3.87 ppm). Robustness under independent search software (FragPipe, CCC = 0.998, LoA {+/-}9%) and cross-platform acquisition (Astral, CCC = 0.980, LoA {+/-}18%) remained within predefined {+/-}30% agreement limits. System suitability criteria were derived empirically from validation performance. This is the first prospective ICH Q2(R2)-aligned validation of untargeted proteomics for HCP quantification, with a statistical framework applicable to other high-dimensional analytical methods requiring regulatory qualification. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/710150v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@1f5331aorg.highwire.dtl.DTLVardef@ee2234org.highwire.dtl.DTLVardef@798eaorg.highwire.dtl.DTLVardef@c84034_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Definitive benchmarking of DDA and DIA for host cell protein analysis on the Orbitrap Astral in a regulatory-aligned framework

Host cell proteins (HCPs) are critical quality attributes in biotherapeutics and require accurate, protein-resolved quantification beyond the coverage limits of immunoassays. The Orbitrap Astral mass spectrometer was evaluated for label-free HCP analysis through a direct comparison of data-dependent acquisition (DDA, Top80) and data-independent acquisition (DIA, 4 m/z windows). Deterministic protein inference was implemented to ensure invariant protein grouping across datasets and software versions. Quantification was anchored using a whole-proteome stable isotope-labeled HCP standard, with identification error controlled through empirical false discovery proportion estimation. Both acquisition modes quantified total HCP content with high linearity (R2 > 0.99) and total error within {+/-}30% acceptance limits across a seven-point spike-in series. DIA achieved greater analytical depth, identifying 45% more proteins and 68% more peptides than DDA, with substantially reduced missingness. Protein-level fold-change behavior was evaluated using hierarchical Bayesian regression, with slopes centered near unity for DIA and systematic compression observed for DDA. Abundance-stratified resampling analysis demonstrated trueness and precision across the dynamic range and defined lower limits of quantification of approximately 0.6 ppm for DIA and 1.6 ppm for DDA. Both acquisition strategies accurately report global HCP content, while DIA provides improved coverage, fold-change fidelity, and sensitivity for low-abundance impurities. This study demonstrates that untargeted MS-based HCP measurements can be analytically qualified for use in regulated biopharmaceutical settings.

biochemistry↗

bioRxiv2024

Comparative analysis of MS/MS search algorithms in label-free shotgun proteomics for monitoring host-cell proteins using trapped ion mobility and ddaPASEF

Host cell proteins (HCPs) are critical quality attributes that can impact the safety, efficacy, and quality of biotherapeutics. Label-free shotgun proteomics is a vital approach for HCP monitoring, yet the choice of tandem mass spectrometry (MS/MS) search algorithms directly influences identification depth and quantification reliability. In this study, six prominent MS/MS search tools--Mascot, MaxQuant, SpectroMine, FragPipe, Byos, and PEAKS--were systematically benchmarked for their performance on complex samples spiked with isotopically labeled proteins from Chinese hamster ovary cells, using trapped ion mobility spectrometry and parallel accumulation-serial fragmentation in data-dependent acquisition mode. Key performance metrics, including peptide and protein identifications, data extraction precision, fold-change (FC) accuracy, linearity, and measurement trueness, were evaluated. A Bayesian modeling framework with Hamiltonian Monte Carlo sampling was employed to robustly estimate FC means and variances, alongside local false discovery rates through posterior probability calibration. Bayesian decision theory, implemented via expected utility maximization, was used to balance accuracy against posterior uncertainty, providing a probabilistic assessment of each tools performance. Through this cumulative analysis, variability across tools was observed: some excelled in identification sensitivity and protein coverage, others in quantitative accuracy with minimal bias, and a few offered balanced performance across metrics. This study establishes a rigorous, data-driven framework for tool benchmarking, delivering insights for selecting MS/MS tools suited to HCP monitoring in biopharmaceutical development. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/621185v2_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@294a82org.highwire.dtl.DTLVardef@dabdb6org.highwire.dtl.DTLVardef@dd2446org.highwire.dtl.DTLVardef@7889c0_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2023

Characterization and Validation of a Middle-Down Hydrophobic Interaction Chromatography Method to Monitor Methionine Oxidation in IgG1

Post-translational modifications (PTMs) of therapeutic monoclonal antibodies (mAbs) can impact the efficacy of a drug. Methionine oxidation can alter the overall hydrophobicity of an antibody, thereby inducing conformational changes and affecting its biological activity. To ensure high quality, safety, and efficacy of mAbs, routine monitoring of PTMs such as methionine (Met) oxidation is essential. Met oxidation in the fragment crystallizable (Fc) region of immunoglobulin-G1 (IgG1) is a critical quality attribute because it impacts not only the interaction with the neonatal Fc receptor and protein A but also the half-life of mAbs in serum circulation. Although bottom-up mass spectrometry provides high site specificity, it may have limited application in quality control workflows, and its complicated sample preparation could result in procedure-induced oxidation. In this study, we describe the development and characterization of a rapid and robust middle-down hydrophobic interaction chromatography method for monitoring Met oxidation in the Fc region of IgG1. Additionally, we assessed a comprehensive method validation package and demonstrated the specificity, linearity, precision, and accuracy of the new method within a range of 3.8-37.7%. The relative quantitative data provided by this method may be used in a regulated workflow to support process and formulation development as well as in the later stages of drug development and batch release and stability studies.

biochemistry↗

bioRxiv2023

Deconfounded Dimension Reduction via Partial Embeddings

Dimension reduction tools preserving similarity and graph structure such as t-SNE and UMAP can capture complex biological patterns in high-dimensional data. However, these tools typically are not designed to separate effects of interest from unwanted effects due to confounders. We introduce the partial embedding (PARE) framework, which enables removal of confounders from any distance-based dimension reduction method. We then develop partial t-SNE and partial UMAP and apply these methods to genomic and neuroimaging data. Our results show that the PARE framework can remove batch effects in single-cell sequencing data as well as separate clinical and technical variability in neuroimaging measures. We demonstrate that the PARE framework extends dimension reduction methods to highlight biological patterns of interest while effectively removing confounding effects.

neuroscience↗

bioRxiv2022

Unexpected long-term retention of subcutaneous beeswax implants and additional notes on dose and composition from four testosterone implant studies

Experimental manipulations of testosterone have advanced our understanding of the hormonal control of traits across vertebrates. Implants are commonly used to supplement testosterone and other hormones to organisms, as they can be readily scaled to produce desired hormone levels in circulation. Concerns about pharmacological (i.e. unnatural) doses of traditional silastic implants led to innovation in implant methods, with time-release pellets and beeswax implants proposed as solutions. A study comparing silastic, time-release pellets, and beeswax implants found the latter to be most effective in delivering a physiologically relevant dose. One proposed advantage to subcutaneous beeswax implants is that they are expected to degrade within the body, thus removing the obligation to recapture implanted individuals in the field. However, few studies have reported on dosage and no published literature has examined the assumption that beeswax implants readily degrade as expected. Here we present time-release androgen data in relation to implants containing varying levels of testosterone from four separate implant studies. In addition, we report long-term persistence of subcutaneous implants, including two cases of implants being retained for > 2 years. Finally, we offer recommendations on the composition and implementation of beeswax implants to aid the pursuit of minimally invasive and physiologically relevant manipulations of circulating hormones.

animal behavior and cognition↗

bioRxiv2022

Phytochromes mediate germination inhibition under red, far-red, and white light in Aethionema arabicum

The view on the role of light during seed germination stems mainly from studies with Arabidopsis, where light is required to initiate this process. In contrast, white light is a strong inhibitor of germination in other plants, exemplified by accessions of Aethionema arabicum, another Brassicaceae. Their seeds respond to light with gene expression changes of key regulators converse to Arabidopsis, resulting in antipodal hormone regulation and prevention of germination. The photoreceptors involved in this process in A. arabicum were unknown. Screening the first mutant collection of A. arabicum, we identified koy-1, a mutant that lost light inhibition of germination, due to a deletion in the promoter of HEME OXYGENASE 1, the gene for a key enzyme in the biosynthesis of the phytochrome chromophore. koy-1 seeds are unresponsive to red- and far-red light and hyposensitive under white light. Comparison of hormone and gene expression between wild type and koy- 1 revealed that very low light fluence stimulates germination, while high irradiance of red and far-red light is inhibitory, indicating a dual role of phytochromes in light-regulated seed germination. The mutation also affects the ratio between the two fruit morphs of A. arabicum, suggesting that light reception via phytochromes can fine-tune several parameters of propagation in adaptation to conditions in the habitat. One sentence summaryCharacterization of a phytochrome chromophore biosynthesis mutant demonstrates an active role of phytochromes in the light-inhibited seed germination in Aethionema arabicum.

plant biology↗

bioRxiv2022

Characterization of environmental effects on flowering and plant architecture in an everbearing strawberry F1-hybrid by meristem dissection and gene expression analysis

Floral transition in the cultivated everbearing strawberry is a hot topic because these genotypes flower perpetually and are difficult to maintain in a non-flowering state. However, it has rarely been studied using morphogenetic and molecular analyses simultaneously. We therefore examined morphogenetic effects and the activation of genes involved in floral induction and initiation in seedlings of an everbearing F1-hybrid. Seedlings were grown at 12, 19, and 26{degrees}C under 10-h SD and 20-h LD conditions. We observed a strong environmental influence on meristem development and a FLOWERING LOCUS T1 (FaFT1)-SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (FaSOC1) pathway similar to that in the everbearing woodland strawberry. The everbearing cultivar showed typical features of a quantitative LD plant, flowering earlier under LD than SD conditions at all temperatures. We also found that floral induction is facilitated by FaFT1 upregulation under LD conditions, while FaSOC1 upregulation in the apex leads to photoperiod-independent floral initiation. Moreover, we confirmed the strawberry meristem identity gene FRUITFULL (FaFUL) can also be used as an early indicator of floral initiation in EB cultivars. This study also highlights the advantages of using seed-propagated F1-hybrids for genetic studies because are genetically identical, and not biased by a previous flowering history.

plant biology↗

bioRxiv2022

Inter-scanner brain MRI volumetric biases persist even in a harmonized multi-subject study of multiple sclerosis

Background/PurposeMulticenter study designs involving a variety of MRI scanners have become increasingly common. However, these present the issue of biases in image-based measures due to scanner or site differences. To assess these biases, we imaged 11 volunteers with multiple sclerosis (MS) with scan and rescan data at 4 sites. Materials and MethodsImages were acquired on Siemens or Philips scanners at 3-tesla. Automated white matter lesion detection and whole brain, gray and white matter, and thalamic volumetry were performed, as well as expert manual delineations of T1 and T2 (FLAIR) lesions. Random effect and permutation-based nonparametric modeling was performed to assess differences in estimated volumes within and across sites. ResultsRandom effect modeling demonstrated model assumption violations for most comparisons of interest. Non-parametric modeling indicated that site explained > 50% of the variation for most estimated volumes. This expanded to > 75% when data from both Siemens and Philips scanners were included. Permutation tests revealed significant differences between average inter- and intra-scanner differences in most estimated brain volumes (P < .05). The automatic activation of spine coil elements during some acquisitions resulted in a shading artifact in these images. Permutation tests revealed significant differences between thalamic volume measurements from acquisitions with and without this artifact. ConclusionDifferences in brain volumetry persisted across MR scanners despite protocol harmonization. These differences were not well explained by variance component modeling; however, statistical innovations for mitigating inter-scanner differences show promise in reducing biases in multi-center studies of MS.

neuroscience↗