Somatic structural variants drive distinct modes of oncogenesis in melanoma.

The diversity of structural variants (SVs) in melanoma and how they impact oncogenesis are incompletely known. We performed harmonized analysis of SVs across melanoma histologic and genomic subtypes, and we identified distinct global properties between subtypes. These included the frequency and size of SVs and SV classes, their relation to chromothripsis events, and the impact on cancer-related genes of SVs that alter topologically associated domain (TAD) boundaries. Following our prior identification of double-stranded break repair deficiency in a subset of triple-wild-type cutaneous melanoma, we identified MRE11 and NBN loss-of-function SVs in melanomas with this mutational signature. Experimental knockouts of MRE11 and NBN, followed by olaparib cell viability assays in melanoma cells, indicated that dysregulation of each of these genes may cause sensitivity to PARP inhibitors in cutaneous melanomas. Broadly, harmonized analysis of melanoma SVs revealed distinct global genomic properties and molecular drivers, which may have biological and therapeutic impact.

Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states.

Clear cell renal cell carcinoma (ccRCC) is molecularly heterogeneous, immune infiltrated, and selectively sensitive to immune checkpoint inhibition (ICI). However, the joint tumor-immune states that mediate ICI response remain elusive. We develop spatially aware deep-learning models of tumor and immune features to learn representations of ccRCC tumors using diagnostic whole-slide images (WSIs) in untreated and treated contexts (n = 1,102 patients). We identify patterns of grade heterogeneity in WSIs not achievable through human pathologist analysis, and these graph-based "microheterogeneity" structures associate with PBRM1 loss of function and with patient outcomes. Joint analysis of tumor phenotypes and immune infiltration identifies a subpopulation of highly infiltrated, microheterogeneous tumors responsive to ICI. In paired multiplex immunofluorescence images of ccRCC, microheterogeneity associates with greater PD1 activation in CD8+ lymphocytes and increased tumor-immune interactions. Our work reveals spatially interacting tumor-immune structures underlying ccRCC biology that may also inform selective response to ICI.

Intertumoral lineage diversity and immunosuppressive transcriptional programs in well-differentiated gastroenteropancreatic neuroendocrine tumors.

Neuroendocrine tumors (NETs) are rare cancers that most often arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic (GEP)-NET growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we investigated the single-cell transcriptomes of tumor and immune cells from patients with gastroenteropancreatic NETs. Malignant GEP-NET cells expressed genes and regulons associated with normal, gastrointestinal endocrine cell differentiation, and fate determination stages. Tumor and lymphoid compartments sparsely expressed immunosuppressive targets commonly investigated in clinical trials, such as the programmed cell death protein-1/programmed death ligand-1 axis. However, infiltrating myeloid cell types within both primary and metastatic GEP-NETs were enriched for genes encoding other immune checkpoints, including VSIR (VISTA), HAVCR2 (TIM3), LGALS9 (Gal-9), and SIGLEC10. Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states.

Clear cell renal cell carcinoma (ccRCC) is molecularly heterogeneous, immune infiltrated, and selectively sensitive to immune checkpoint inhibition (ICI). Established histopathology paradigms like nuclear grade have baseline prognostic relevance for ccRCC, although whether existing or novel histologic features encode additional heterogeneous biological and clinical states in ccRCC is uncertain. Here, we developed spatially aware deep learning models of tumor- and immune-related features to learn representations of ccRCC tumors using diagnostic whole-slide images (WSI) in untreated and treated contexts (n = 1102 patients). We discovered patterns of nuclear grade heterogeneity in WSI not achievable through human pathologist analysis, and these graph-based "microheterogeneity" structures associated with PBRM1 loss of function, adverse clinical factors, and selective patient response to ICI. Joint computer vision analysis of tumor phenotypes with inferred tumor infiltrating lymphocyte density identified a further subpopulation of highly infiltrated, microheterogeneous tumors responsive to ICI. In paired multiplex immunofluorescence images of ccRCC, microheterogeneity associated with greater PD1 activation in CD8+ lymphocytes and increased tumor-immune interactions. Thus, our work reveals novel spatially interacting tumor-immune structures underlying ccRCC biology that can also inform selective response to ICI.

A reciprocal translocation involving Aspergillus nidulans snxAHrb1/Gbp2 and gyfA uncovers a new regulator of the G2-M transition and reveals a role in transcriptional repression for the setBSet2 histone H3-lysine-36 methyltransferase.

Aspergillus nidulans snxA, an ortholog of Saccharomyces cerevisiae Hrb1/Gbp2 messenger RNA shuttle proteins, is-in contrast to budding yeast-involved in cell cycle regulation, in which snxA1 and snxA2 mutations as well as a snxA deletion specifically suppress the heat sensitivity of mutations in regulators of the CDK1 mitotic induction pathway. snxA mutations are strongly cold sensitive, and at permissive temperature snxA mRNA and protein expression are strongly repressed. Initial attempts to identify the causative snxA mutations revealed no defects in the SNXA protein. Here, we show that snxA1/A2 mutations resulted from an identical chromosome I-II reciprocal translocation with breakpoints in the snxA first intron and the fourth exon of a GYF-domain gene, gyfA. Surprisingly, a gyfA deletion and a reconstructed gyfA translocation allele suppressed the heat sensitivity of CDK1 pathway mutants in a snxA+ background, demonstrating that 2 unrelated genes, snxA and gyfA, act through the CDK1-CyclinB axis to restrain the G2-M transition, and for the first time identifying a role in G2-M regulation for a GYF-domain protein. To better understand snxA1/A2-reduced expression, we generated suppressors of snxA cold sensitivity in 2 genes: (1) loss of the abundant nucleolar protein Nsr1/nucleolin bypassed the requirement for snxA and (2) loss of the Set2 histone H3 lysine36 (H3K36) methyltransferase or a nonmethylatable histone H3K36L mutant rescued hypomorphic snxA mutants by restoring full transcriptional proficiency, indicating that methylation of H3K36 acts normally to repress snxA transcription. These observations are in line with known Set2 functions in preventing excessive and cryptic transcription of active genes.