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PD-1 pathway blockade in combination with chemotherapy has emerged as a treatment paradigm for patients with resectable lung cancer, but insights into predictive biomarkers and mechanisms of immune responses are lacking. A study uses spatial transcriptomic methods to identify patterns within the tumor microenvironment associated with response.

Samples from 19 patients with non-small-cell lung cancer treated with a combination of chemotherapy and immune checkpoint blockade are profiled with single-cell RNA sequencing and spatial transcriptomics to identify factors associated with treatment resistance.

Existing functional genomics datasets are European-centric. The Asian Immune Diversity Atlas incorporated single-cell RNA-sequencing data from approximately 1 million peripheral blood mononuclear cells from around 500 donors of diverse Asian ancestries. Mapping of splicing quantitative trait loci revealed context-specific regulation of alternative splicing, as well as cell-type and ancestry-specific genetic effects on complex diseases.

The SCHEMATIC resource combines CRISPR pairwise gene knockout experiments across tumor cell types with large-scale drug sensitivity assays to identify a core network of highly penetrant, synthetic lethal genetic interactions that can help to match individuals with cancer to targeted therapies.

This analysis of single-cell RNA sequencing data from peripheral blood mononuclear cells for 474 individuals of diverse Asian ancestries in the Asian Immune Diversity Atlas links cell-type-specific splicing variation with autoimmune and inflammatory disease risk.

Using reported parental disease history to decipher the genetics of Alzheimer’s disease may be promising, but this approach is also susceptible to complex selection and information bias that can mislead researchers if not accounted for.

Multi-ancestry genome-wide analyses identify new risk loci for age-related macular degeneration. Ancestry-specific analyses identify distinct effects at major risk loci, including smaller effect sizes for CFH risk alleles in haplotypes of African ancestry.

A novel method for analyzing single-cell genomics enables direct inference of cell cycle and proliferation status, highlighting the diversity of proliferation rates in clonal cancer. This approach opens a new avenue for high-resolution exploration of the role of proliferation in cancer evolution at the single-cell level.

Single-cell Proliferation Rate Inference in Non-homogeneous Tumors through Evolutionary Routes (SPRINTER) allows users to infer proliferation rates of individual clones within a tumor from single-cell DNA sequencing data. Applying SPRINTER to human tumor datasets highlighted a link between proliferation and metastatic potential.

Advancements in single-cell analysis technologies are enabling exploration of the intricacies of the human brain at unprecedented resolution. However, most research thus far has focused on the adult brain. Here, these tools are applied to reveal cell-type-specific gene-expression dynamics as the brain grows from childhood to adulthood.

Chromosomal instability plays a crucial part in tumor progression, shaping cancer cell phenotypes and driving treatment resistance. We harnessed two single-cell multiomics methods to characterize the heterogeneity of acute myeloid leukemia with complex karyotype (CK-AML). Our data link genetic, non-genetic and functional heterogeneity and reveal intriguing therapeutic sensitivities.

PopV is an ensemble method for cell type labeling in single-cell genomics. A Cell Ontology-inspired voting procedure across different algorithms highlights low confidence annotations, thereby guiding human-in-the loop components of the annotation process.

Using single-cell whole-genome sequencing, we reveal the landscape of copy number alterations in normal breast tissue from both BRCA carriers and wild-type individuals.

Perez, Goronzy et al. present ChIP-DIP, which enables multiplex genomic mapping of hundreds of epitopes from a single sample. The authors apply ChIP-DIP to localize modified histones, transcription factors and other chromatin-interacting proteins at scale, in both cell lines and primary cells.

Alzheimer’s disease is a complex, heterogeneous disorder with multiple genetic subtypes. Spatial and single-cell gene expression analyses of these subtypes have provided new insights into general and subtype-specific cellular and molecular mechanisms of Alzheimer’s disease.