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Graphical abstract, Lung adenocarcinoma (LUAD) has a high mortality rate and is difficult to diagnose and treat in its early stage. Previous studies have demonstrated that small nucleolar RNAs (snoRNAs) play a critical role in tumor immune infiltration and the development of a variety of solid tumors. However, there have been no studies on the correlation between tumor-infiltrating immune-related snoRNAs (TIISRs) and LUAD. In this study, we filtered six immune-related snoRNAs based on the tissue specificity index (TSI) and expression profile of all snoRNAs between all LUAD cell lines from the Cancer Cell Line Encyclopedia and 21 types of immune cells from the Gene Expression Omnibus database. Further, we performed real-time quantitative polymerase chain reaction (RT-qPCR) to validate the expression status of these snoRNAs on peripheral blood mononuclear cells (PBMCs) and lung cancer cell lines. Next, we developed a TIISR signature based on the expression profiles of snoRNAs from 479 LUAD patients filtered by the random survival forest algorithm. We then analyzed the value of this TIISR signature (TIISR risk score) for assessing tumor immune infiltration, immune checkpoint inhibitor (ICI) treatment response, and the prognosis of LUAD between groups with high and low TIISR risk score. Further, we found that the TIISR risk score groups showed significant differences in biological characteristics and that the risk score could be used to assess the level of tumor immune cell infiltration, thereby predicting prognosis and responsiveness to immunotherapy in LUAD patients.

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings., Graphical Abstract, Highlights • Integrating protein interaction data with metabolic models expands multiomic mapping. • Proteomic profiling of tumors and cell lines reveals altered metabolic-related signatures. • Metabolite measurements validate pathway alterations in cancer cell lines and tumors., In Brief Metabolism is recognized as an important driver of complex diseases, but global metabolite profiling remains a challenge. Protein expression is a poor proxy because pathway enrichment models provide an incomplete mapping between the proteome and metabolism. We developed MOMENTA, a multiomic network approach for interrogating metabolic pathways from proteomics data. Analysis of data from cancer cell lines and human tumors reveals metabolic network rewiring and oncogene connections. The metabolic networks altered in cancer are linked to clinical outcomes.

Breast cancer cells that have undergone partial epithelial–mesenchymal transition (EMT) are believed to be more invasive than cells that have completed EMT. To study metabolic reprogramming in different mesenchymal states, we analyzed protein expression following EMT in the breast epithelial cell model D492 with single-shot LFQ supported by a SILAC proteomics approach. The D492 EMT cell model contains three cell lines: the epithelial D492 cells, the mesenchymal D492M cells, and a partial mesenchymal, tumorigenic variant of D492 that overexpresses the oncogene HER2. The analysis classified the D492 and D492M cells as basal-like and D492HER2 as claudin-low. Comparative analysis of D492 and D492M to tumorigenic D492HER2 differentiated metabolic markers of migration from those of invasion. Glutamine-fructose-6-phosphate transaminase 2 (GFPT2) was one of the top dysregulated enzymes in D492HER2. Gene expression analysis of the cancer genome atlas showed that GFPT2 expression was a characteristic of claudin-low breast cancer. siRNA-mediated knockdown of GFPT2 influenced the EMT marker vimentin and both cell growth and invasion in vitro and was accompanied by lowered metabolic flux through the hexosamine biosynthesis pathway (HBP). Knockdown of GFPT2 decreased cystathionine and sulfide:quinone oxidoreductase (SQOR) in the transsulfuration pathway that regulates H2S production and mitochondrial homeostasis. Moreover, GFPT2 was within the regulation network of insulin and EGF, and its expression was regulated by reduced glutathione (GSH) and suppressed by the oxidative stress regulator GSK3-β. Our results demonstrate that GFPT2 controls growth and invasion in the D492 EMT model, is a marker for oxidative stress, and associated with poor prognosis in claudin-low breast cancer., Graphical Abstract, Highlights • GFPT2 is upregulated following EMT. • GFPT2 is a marker for claudin-low breast cancer. • GFPT2 affects vimentin, cell proliferation, and cell invasion. • GFPT2 responds to oxidative stress. • GFPT2 is regulated by insulin and EGF., In Brief Epithelial–mesenchymal transition (EMT) is a cellular process inherent to cancer cell metastasis. Metabolic reprogramming is a driver of EMT. We performed proteomic profiling of three isogenic cell lines from human breast epithelium representing the epithelial, mesenchymal, and “partial” mesenchymal states of EMT to identify metabolic vulnerabilities associated with cell invasion. Bioinformatic and functional analysis revealed that the metabolic enzyme GFPT2 is a marker of claudin-low breast cancer, responds to oxidative stress, and impacts EMT, cell growth, and cell invasion.

Background: There is an urgent need for the identification of new, clinically useful biomarkers of CRC to enhance diagnostic and prognostic capabilities. Methods: We performed proteomic profiling on serum samples from paired pre- and post-operative CRC patients, colorectal polyps patients and healthy controls using an approach combining magnetic bead-based weak cation exchange and matrix-assisted laser desorption ionization-time of flight mass spectrometry. We next performed liquid chromatography-electrospray ionization-tandem mass spectrometry to identify the proteins and selected potential biomarker based on bioinformatics analysis of the TCGA and GEO dataset. We examined SETD7 expression in serum and tissue samples by ELISA and immunohistochemistry respectively and explored the biological function of SETD7 in vitro. Findings: 85 differentially expressed peptides were identified. Five peptides showing the most significant changes in abundance across paired pre- and post-operation CRC patients, colorectal polyps patients and healthy controls were identified as peptide regions of FGA, MUC5AC and SETD7. Bioinformatics analysis suggested that the up-regulation of SETD7 in CRC is relatively specific. Validation studies showed that SETD7 expression increased from healthy controls to those with colorectal polyps and finally CRC patients, and decreased after surgery. The sensitivity and specificity of SETD7 were 92.17% and 81.08%, with a high diagnostic value (AUC = 0.9477). In addition, SETD7 expression was significantly correlated with tumor stage and microsatellite instability. Knockdown of SETD7 inhibited cancer cell proliferation, induced G1/S cell cycle arrest and increased apoptosis. Interpretation: Our data indicate that SETD7 could serve as a potential diagnostic and prognostic biomarker for CRC. Keywords: Colorectal cancer, Proteomics, Serum biomarker, SETD7

Graphical abstract, Highlights • Expressions of ACE2 and TMPRSS2 were observed in the extrapulmonary organs. • Direct infections of SARS-CoV-2 in extrapulmonary organs were observed in patients with COVID-19. • Clinical manifestation and management for extrapulmonary organ injuries in COVID-19 should be noticed. • There might be a relationship between the infection of extrapulmonary organs and positive SARS-CoV-2 test in recovered patients., At the end of 2019, the coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in China. Currently, it is breaking out globally and posing a serious threat to public health. The typically clinical characteristics of COVID-19 patients were fever and respiratory symptoms, and a proportion of patients were accompanied by extrapulmonary symptoms including cardiac injury, kidney injury, liver injury, digestive tract injury, and neurological symptoms. Angiotensin converting enzyme 2 (ACE2) has been proven to be a major receptor for SARS-CoV-2 and could mediate virus entry into cells. And transmembrane protease serine 2 (TMPRSS2) could cleave the spike (S) protein of SARS-CoV-2, which facilitates the fusion of SARS-CoV-2 and cellular membranes. The mRNA expressions of both ACE2 and TMPRSS2 were observed in the heart, digestive tract, liver, kidney, brain and other organs. SARS-CoV-2 may have a capacity to infect extrapulmonary organs due to the expressions of ACE2 and TMPRSS2 in the cells and tissues of these organs. It seems that there is a potential involvement of ACE2 and TMPRSS2 expressions in the virus infection of extrapulmonary organs and the manifestation of symptoms related to these organs in patients with COVID-19. Here, we revealed the expressions of ACE2 and TMPRSS2 in extrapulmonary organs, and we also summarized the clinical manifestation and the management of extrapulmonary complications in patients with COVID-19.

NADPH oxidase 4 (NOX4) is a redox active, membrane-associated protein that contributes to genomic instability, redox signaling, and radiation sensitivity in human cancers based on its capacity to generate H2O2 constitutively. Most studies of NOX4 in malignancy have focused on the evaluation of a small number of tumor cell lines and not on human tumor specimens themselves; furthermore, these studies have often employed immunological tools that have not been well characterized. To determine the prevalence of NOX4 expression across a broad range of solid tumors, we developed a novel monoclonal antibody that recognizes a specific extracellular region of the human NOX4 protein, and that does not cross-react with any of the other six members of the NOX gene family. Evaluation of 20 sets of epithelial tumors revealed, for the first time, high levels of NOX4 expression in carcinomas of the head and neck (15/19 patients), esophagus (12/18 patients), bladder (10/19 patients), ovary (6/17 patients), and prostate (7/19 patients), as well as malignant melanoma (7/15 patients) when these tumors were compared to histologically-uninvolved specimens from the same organs. Detection of NOX4 protein upregulation by low levels of TGF-β1 demonstrated the sensitivity of this new probe; and immunofluorescence experiments found that high levels of endogenous NOX4 expression in ovarian cancer cells were only demonstrable associated with perinuclear membranes. These studies suggest that NOX4 expression is upregulated, compared to normal tissues, in a well-defined, and specific group of human carcinomas, and that its expression is localized on intracellular membranes in a fashion that could modulate oxidative DNA damage., Graphical abstract fx1, Highlights • NADPH oxidase 4 (NOX4) detection has been achieved with a monoclonal antibody (47-6) developed to the extracellular E-loop region (amino acids 209–282). • Tissue microarray analysis of 20 human malignancies reveals differential NOX4 expression by IHC was higher in bladder, esophageal, head and neck, ovary, and prostate cancers and melanoma than in normal tissues. • NOX4 expression in the ovarian cancer cell line COV362 is localized in the perinuclear region.

Cancer cell lines are a tremendous resource for cancer biology and therapy development. These multipurpose tools are commonly used to examine the genetic origin of cancers, to identify potential novel tumor targets, such as tumor antigens for vaccine devel-opment, and utilized to screen potential therapies in preclinical studies. Mutations, gene expression, and drug sensitivity have been determined for many cell lines using next-generation sequencing (NGS). However, the human leukocyte antigen (HLA) type and HLA expression of tumor cell lines, characterizations necessary for the development of cancer vaccines, have remained largely incomplete and, such information, when available, has been distributed in many publications. Here, we determine the 4-digit HLA type and HLA expression of 167 cancer and 10 non-cancer cell lines from publically available RNA-Seq data. We use standard NGS RNA-Seq short reads from "whole transcriptome" sequencing, map reads to known HLA types, and statistically determine HLA type, heterozygosity, and expression. First, we present previously unreported HLA Class I and II genotypes. Second, we determine HLA expression levels in each cancer cell line, providing insights into HLA downregulation and loss in cancer. Third, using these results, we provide a fundamental cell line "barcode" to track samples and prevent sample annotation swaps and contamination. Fourth, we integrate the cancer cell-line specific HLA types and HLA expression with available cell-line specific mutation information and existing HLA binding prediction algorithms to make a catalog of predicted antigenic mutations in each cell line. The compilation of our results are a fundamental resource for all researchers selecting specific cancer cell lines based on the HLA type and HLA expression, as well as for the development of immunotherapeutic tools for novel cancer treatment modalities.