Search

The associated publication reports proteogenomic analysis of non-small cell lung cancer, where we identified molecular subtypes with distinct immune evasion mechanisms and therapeutic targets, and validated our classification method in separate clinical cohorts. This protocol describes histological, tertiary lymphoid structure (TLS), and immunohistochemical evaluation of clinical samples. Specifically, immunohistochemistry was performed for PD-L1, CD3, and CD8 on tumor microarrays (TMAs) derived from formalin-fixed paraffin embedded (FFPE) samples.

The associated publication reports proteogenomic analysis of non-small cell lung cancer (NSCLC), where we identified molecular subtypes with distinct immune evasion mechanisms and therapeutic targets, and validated our classification method in separate clinical cohorts. This protocol describes sections of the bioinformatics analysis of the multi-omics data, namely, data analysis and processing for panel sequencing, identification of cancer- and driver-related proteins in proteomics data, proteogenomics search, and machine learning-based classifiers for NSCLC subtyping. Specifically, a cohort classifier was built using support-vector machine-recursive feature elimination (SVM-RFE) algorithm applied to in-depth proteomics data from a cohort of 141 samples. The classifier was then validated in three external datasets. Another classifier, suitable for single-sample subtyping, was built using k-top scoring pairs (k-TSP) algorithm applied to label-free data from a cohort of 136 samples. The k-TSP-based classifier was validated in two independent cohorts and an additional external dataset.

The associated publication reports proteogenomic analysis of non-small cell lung cancer (NSCLC), where we identified molecular subtypes with distinct immune evasion mechanisms and therapeutic targets, and validated our classification method in separate clinical cohorts. The in-depth proteomic analysis pointed to a potential role of STK11 inactivation in liver-specific signaling and subsequent cancer growth and immune evasion mechanisms. This protocol describes in vitro validation of the downstream effects of STK11-AMPK signaling on HNF1A and FGL1 in a liver and two lung cancer cell lines.

The associated publication reports proteogenomic analysis of non-small cell lung cancer, where we identified molecular subtypes with distinct immune evasion mechanisms and therapeutic targets, and validated our classification method in separate clinical cohorts. This protocol describes the sample preparation and mass spectrometry (MS)-based in-depth and rapid proteomic analyses of tumor and biopsy samples. We deployed single-pot solid-phase-enhanced sample preparation (SP3). For the in-depth analysis, we used TMT labeling, followed by high-resolution isoelectric focusing (HiRIEF) prefractionation and LC-MS with data-dependent acquisition (DDA). The reported protocol achieved analytical depth of close to 14,000 quantified proteins and almost 10,000 across the entire cohort of 141 samples. The rapid analysis was label-free, based on LC-MS with data-independent acquisition (DIA). The median number of identified proteins was 3,967 and 3,552 in two independent cohorts of tumor samples (n = 141 and 208, respectively), and 2,494 in another cohort of biopsy material (n = 84).

We have implemented the pypgatk package and the pgdb workflow to create proteogenomics databases based on ENSEMBL resources. The tools allow the generation of protein sequences from novel protein-coding transcripts by performing a three-frame translation of pseudogenes, lncRNAs and other non-canonical transcripts, such as those produced by alternative splicing events. It also includes exonic out-of-frame translation from otherwise canonical protein-coding mRNAs. Moreover, the tool enables the generation of variant protein sequences from multiple sources of genomic variants including COSMIC, cBioportal, gnomAD and mutations detected from sequencing of patient samples. pypgatk and pgdb provide multiple functionalities for database handling including optimized target/decoy generation by the algorithm DecoyPyrat. Finally, we have reanalyzed six public datasets in PRIDE by generating cell-type specific databases for 65 cell lines using the pypgatk and pgdb workflow, revealing a wealth of non-canonical or cryptic peptides amounting to5% of the total number of peptides identified.The software is freely available. pypgatk: https://github.com/bigbio/py-pgatk/ and pgdb: https://nf-co.re/pgdb.Supplementary data are available at Bioinformatics online.

Previous evidence from post-mortem Alzheimer disease (AD) brains and drug (especially rapamycin)-oriented in vitro and in vivo models implicated an aberrant accumulation of the mammalian target of rapamycin (mTor) in tangle-bearing neurons in AD brains and its role in the formation of abnormally hyperphosphorylated tau. Compelling evidence indicated that the sequential molecular events such as the synthesis and phosphorylation of tau can be regulated through p70 S6 kinase, the well characterized immediate downstream target of mTor. In the present study, we further identified that the active form of mTor per se accumulates in tangle-bearing neurons, particularly those at early stages in AD brains. By using mass spectrometry and Western blotting, we identified three phosphoepitopes of tau directly phosphorylated by mTor. We have developed a variety of stable cell lines with genetic modification of mTor activity using SH-SY5Y neuroblastoma cells as background. In these cellular systems, we not only confirmed the tau phosphorylation sites found in vitro but also found that mTor mediates the synthesis and aggregation of tau, resulting in compromised microtubule stability. Changes of mTor activity cause fluctuation of the level of a battery of tau kinases such as protein kinase A, v-Akt murine thymoma viral oncogene homolog-1, glycogen synthase kinase 3β, cyclin-dependent kinase 5, and tau protein phosphatase 2A. These results implicate mTor in promoting an imbalance of tau homeostasis, a condition required for neurons to maintain physiological function.