Resources

Qui et al. perform co-detection by indexing profiling of 401 hepatocellular carcinoma patient samples and identify a role for vimentin^high macrophages in instructing an immune-suppressive microenvironment by enhancing the suppressive activity of regulatory T cells via interleukin-1β.

Dong et al. present an integrative proteogenomic analysis of high-risk prostate cancer samples from a cohort of Chinese patients and highlight potential therapeutic vulnerabilities and diagnostic markers.

Liang and colleagues establish a high-quality protein expression resource for 8,000 The Cancer Genome Atlas patient samples and 900 Cancer Cell Line Encyclopedia cell lines for approximately 450 proteins, which they use to identify synthetic lethality pairs and metastasis markers.

Krönke and colleagues present a multiomic resource of plasma cell malignancies, including multiple myeloma, that comprises phosphoproteomics, RNA and DNA sequencing and provides insights into cancer type biology and candidate therapeutic targets.

Shao and colleagues present a multiomic analysis of breast tumor samples from Chinese patients, consisting of genomic, transcriptomic, proteomic, metabolomic, radiomic and digital pathology data.

Ganesan and colleagues characterize T cell clonality and transcriptomes at the single-cell level in pediatric brain tumor samples, providing insights into existing tumor neoantigens and T cell responses and the potential for effective immunotherapy.

Mitsiades and colleagues utilize functional genomics data in over 700 cancer cell lines, to identify genes with preferentially essential functions in multiple myeloma, which may represent targets for precision medicine strategies.

Joyce and colleagues use bulk and single-cell profiling of T cell phenotypes in human samples from primary brain tumors and brain metastases as a resource for understanding the biology and therapeutic relevance of the brain tumor microenvironment.

Snijder and colleagues use ex vivo pharmacoscopy and bone marrow composition profiling in a cohort of patients with multiple myeloma to identify tailored therapeutic sensitivities and stratify the cohort into three microenvironmental PhenoGroups.

Perou and colleagues perform genomic, transcriptomic and epigenetic analyses on pairs of primary and metastatic breast tumors, detecting subtype switching and changes in immune signatures and DNA methylation patterns associated with metastasis.

Baek and colleagues present a proteogenomic analysis of 196 patients with pancreatic adenocarcinoma in an Asian population, identifying subtypes with invasive and proliferative features or immunogenic features, as a resource for future studies.

Wang et. al. perform single-cell and spatial analyses of paired primary and recurrent samples from patients receiving standard-of-care therapy for GBM and find changes in tumor signaling pathways and the microenvironment with targetable potential.

Dubois and colleagues assemble a large cohort of human pediatric high-grade glioma samples, identifying patterns of simple and complex structural variants and characterizing their role in tumor development and evolution.

Skokos and colleagues characterize human early-stage clear cell renal cell carcinoma with single-cell ATAC-seq and RNA-seq, identifying a spectrum of NFκB-promoted T cell dysfunction in the microenvironment and defining a pro-apoptotic signature.

Using genome-wide bisulfite sequencing of acute lymphoblastic leukemia subtypes, cell lines and healthy cells, Hetzel et. al. find that unlike most cancers, ALL has a highly methylated genome, which points to a distinct mode of epigenome regulation in this cancer type.

Welm and colleagues present a biobank of human-derived xenografts and organoids and demonstrate its value for high-throughput drug screening and applied precision medicine.

Zhang and colleagues analyzed patients with lung cancer treated with anti-PD-1 with single-cell methods, finding the presence of precursor exhausted T cells in responders that accumulated through local expansion and clonal revival from peripheral T cells.

Lehtiö and colleagues perform proteogenomic analysis of non-small cell lung cancer and identify molecular subtypes with distinct immune-evasion mechanisms and therapeutic targets and validate their classification method in separate clinical cohorts.

Robbins and colleagues develop and test a machine learning neoantigen ranking model using experimentally validated neoantigens from human tumors, providing a resource of targetable neoantigens for future immunotherapies.

Using single-cell RNA sequencing, CyTOF and multiplex immunohistochemistry, Steele et al. survey the immune landscape in pancreatic cancers, adjacent tissue and blood, observing heterogeneous immune checkpoint receptor expression within patients.