Evaluating Proteomics Imputation Methods with Improved Criteria.

Quantitative measurements produced by tandem mass spectrometry proteomics experiments typically contain a large proportion of missing values. Missing values hinder reproducibility, reduce statistical power, and make it difficult to compare across samples or experiments. Although many methods exist for imputing missing values, in practice, the most commonly used methods are among the worst performing. Furthermore, previous benchmarking studies have focused on relatively simple measurements of error such as the mean-squared error between imputed and held-out values. Here we evaluate the performance of commonly used imputation methods using three practical, "downstream-centric" criteria. These criteria measure the ability to identify differentially expressed peptides, generate new quantitative peptides, and improve the peptide lower limit of quantification. Our evaluation comprises several experiment types and acquisition strategies, including data-dependent and data-independent acquisition. We find that imputation does not necessarily improve the ability to identify differentially expressed peptides but that it can identify new quantitative peptides and improve the peptide lower limit of quantification. We find that MissForest is generally the best performing method per our downstream-centric criteria. We also argue that existing imputation methods do not properly account for the variance of peptide quantifications and highlight the need for methods that do.

Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing.

Lung cancer, the leading cause of cancer mortality, exhibits heterogeneity that enables adaptability, limits therapeutic success, and remains incompletely understood. Single-cell RNA sequencing (scRNA-seq) of metastatic lung cancer was performed using 49 clinical biopsies obtained from 30 patients before and during targeted therapy. Over 20,000 cancer and tumor microenvironment (TME) single-cell profiles exposed a rich and dynamic tumor ecosystem. scRNA-seq of cancer cells illuminated targetable oncogenes beyond those detected clinically. Cancer cells surviving therapy as residual disease (RD) expressed an alveolar-regenerative cell signature suggesting a therapy-induced primitive cell-state transition, whereas those present at on-therapy progressive disease (PD) upregulated kynurenine, plasminogen, and gap-junction pathways. Active T-lymphocytes and decreased macrophages were present at RD and immunosuppressive cell states characterized PD. Biological features revealed by scRNA-seq were biomarkers of clinical outcomes in independent cohorts. This study highlights how therapy-induced adaptation of the multi-cellular ecosystem of metastatic cancer shapes clinical outcomes.

Inferring Tunicate Relationships and the Evolution of the Tunicate Hox Cluster with the Genome of Corella inflata.

Tunicates, the closest living relatives of vertebrates, have served as a foundational model of early embryonic development for decades. Comparative studies of tunicate phylogeny and genome evolution provide a critical framework for analyzing chordate diversification and the emergence of vertebrates. Toward this goal, we sequenced the genome of Corella inflata (Ascidiacea, Phlebobranchia), so named for the capacity to brood self-fertilized embryos in a modified, "inflated" atrial chamber. Combining the new genome sequence for Co. inflata with publicly available tunicate data, we estimated a tunicate species phylogeny, reconstructed the ancestral Hox gene cluster at important nodes in the tunicate tree, and compared patterns of gene loss between Co. inflata and Ciona robusta, the prevailing tunicate model species. Our maximum-likelihood and Bayesian trees estimated from a concatenated 210-gene matrix were largely concordant and showed that Aplousobranchia was nested within a paraphyletic Phlebobranchia. We demonstrated that this relationship is not an artifact due to compositional heterogeneity, as had been suggested by previous studies. In addition, within Thaliacea, we recovered Doliolida as sister to the clade containing Salpida and Pyrosomatida. The Co. inflata genome provides increased resolution of the ancestral Hox clusters of key tunicate nodes, therefore expanding our understanding of the evolution of this cluster and its potential impact on tunicate morphological diversity. Our analyses of other gene families revealed that several cardiovascular associated genes (e.g., BMP10, SCL2A12, and PDE2a) absent from Ci. robusta, are present in Co. inflata. Taken together, our results help clarify tunicate relationships and the genomic content of key ancestral nodes within this phylogeny, providing critical insights into tunicate evolution.