Single-cell-guided identification of logic-gated antigen combinations for designing effective and safe CAR therapy.

Unlabelled: Chimeric antigen receptor (CAR) T-cell therapy has revolutionized the treatment of hematological malignancies. However, its application in solid tumors remains limited because single targets are unlikely to suffice due to tumor antigen heterogeneity and off-tumor toxicities. To overcome these obstacles, we developed , a computational approach that utilizes single-cell transcriptomics data from patient tumors to systematically identify the cancer-specific antigen circuits with logic gates ("AND," "OR," and "NOT") that target the majority of cancer cells in a tumor while sparing normal cells and tissues as much as possible.

Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues.

Metastasis is a leading cause of cancer-related deaths, yet understanding how metastatic tumors adapt from their origin to their target tissues remains a fundamental challenge. To address this, we assessed whether primary and metastatic tumors more closely resemble their tissues of origin or target tissues in terms of gene expression. We analyzed expression profiles from multiple cancer types and normal tissues, including single-cell and bulk RNA sequencing data from both paired and unpaired patient cohorts.

Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues.

Metastasis is a leading cause of cancer-related deaths, yet understanding how metastatic tumors adapt from their origin to target tissues is challenging. To address this, we assessed whether primary and metastatic tumors resemble their tissue of origin or target tissue in terms of gene expression. We analyzed gene expression profiles from various cancer types, including single-cell and bulk RNA-seq data, in both paired and unpaired primary and metastatic patient cohorts.

Pan-Cancer Analysis of Patient Tumor Single-Cell Transcriptomes Identifies Promising Selective and Safe Chimeric Antigen Receptor Targets in Head and Neck Cancer.

Chimeric antigen receptor (CAR) T cell therapies have yielded transformative clinical successes for patients with blood tumors, but their full potential remains to be unleashed against solid tumors. One challenge is finding targets, which we define intuitively to be cell surface proteins that are expressed widely by cancer cells but minimally by healthy cells in the tumor microenvironment and other normal tissues. Analyzing patient tumor single-cell transcriptomics data, we first defined and quantified selectivity and safety scores of existing CAR targets for indications in which they are in clinical trials or approved.

A comprehensive analysis of adverse events in the first 30 days of phase 1 pediatric CAR T-cell trials.

The tremendous success of chimeric antigen receptor (CAR) T cells in children and young adults (CAYAs) with relapsed/refractory B-cell acute lymphoblastic leukemia is tempered by toxicities such as cytokine release syndrome (CRS). Despite expansive information about CRS, profiling of specific end-organ toxicities secondary to CAR T-cell therapy in CAYAs is limited. This retrospective, single-center study sought to characterize end-organ specific adverse events (AEs) experienced by CAYAs during the first 30 days after CAR T-cell infusion.

Correction: CAPN1 is a novel binding partner and regulator of the tumor suppressor NF1 in melanoma.

[This corrects the article DOI: 10.18632/oncotarget.25805.

Publisher Correction: Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma.

In the version of this article originally published, there was an error in the URL linked to by an accession code in the data availability section of the methods. The erroneous URL was: https://www.ncbi.

CAPN1 is a novel binding partner and regulator of the tumor suppressor NF1 in melanoma.

Neurofibromin 1 (NF1), a tumor suppressor that negatively regulates RAS through its GTPase activity, is highly mutated in various types of sporadic human cancers, including melanoma. However, the binding partners of NF1 and the pathways in which it is involved in melanoma have not been characterized in an in depth manner. Utilizing a mass spectrometry analysis of NF1 binding partners, we revealed Calpain1 (CAPN1), a calcium-dependent neutral cysteine protease, as a novel NF1 binding partner that regulates NF1 degradation in melanoma cells.

Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma.

Immune checkpoint blockade (ICB) therapy provides remarkable clinical gains and has been very successful in treatment of melanoma. However, only a subset of patients with advanced tumors currently benefit from ICB therapies, which at times incur considerable side effects and costs. Constructing predictors of patient response has remained a serious challenge because of the complexity of the immune response and the shortage of large cohorts of ICB-treated patients that include both 'omics' and response data.

BeWith: A Between-Within method to discover relationships between cancer modules via integrated analysis of mutual exclusivity, co-occurrence and functional interactions.

The analysis of the mutational landscape of cancer, including mutual exclusivity and co-occurrence of mutations, has been instrumental in studying the disease. We hypothesized that exploring the interplay between co-occurrence, mutual exclusivity, and functional interactions between genes will further improve our understanding of the disease and help to uncover new relations between cancer driving genes and pathways. To this end, we designed a general framework, BeWith, for identifying modules with different combinations of mutation and interaction patterns.

WeSME: uncovering mutual exclusivity of cancer drivers and beyond.

Motivation: Mutual exclusivity is a widely recognized property of many cancer drivers. Knowledge about these relationships can provide important insights into cancer drivers, cancer-driving pathways and cancer subtypes. It can also be used to predict new functional interactions between cancer driving genes and uncover novel cancer drivers.