Biology subjects

Wind-Rotolo, M.

Publications and source records attributed to Wind-Rotolo, M..

3 recordsLinked to original sources

bioRxiv2020

Myeloid cell-associated resistance to PD-1/PD-L1 blockade in urothelial cancer revealed through bulk and single-cell RNA sequencing

Adaptive immunity and tumor-promoting inflammation exist in delicate balance in individual tumor microenvironments; however, the role of this balance in defining sensitivity and resistance to PD-1/PD-L1 blockade therapy in urothelial cancer and other malignancies is poorly understood. We pursued an unbiased systems biology approach using bulk RNA sequencing data to examine pre-treatment molecular features associated with sensitivity to PD-1/PD-L1 blockade in patients with metastatic urothelial cancer and identified an adaptive_immune_response module associated with response and an inflammatory_response module and stromal module associated with resistance. We mapped these gene modules onto single-cell RNA sequencing data demonstrating the adaptive_immune_response module emanated predominantly from T, NK, and B cells, the inflammatory_response module from monocytes/macrophages, and the stromal module from fibroblasts. The adaptive_immune_response:inflammatory_response module expression ratio in individual tumors, reflecting the balance between antitumor immunity and tumor-associated inflammation and coined the 2IR score, best correlated with clinical outcomes and was validated in an independent cohort. Individual monocytes/macrophages with low 2IR scores demonstrated upregulation of proinflammatory genes including IL1B and downregulation of antigen presentation genes, were unrelated to classical M1 versus M2 polarization, and were enriched in pre-treatment peripheral blood from patients with PD-L1 blockade-resistant metastatic urothelial cancer. Single sentence summaryProinflammatory monocytes/macrophages, present in tumor and blood, are associated with resistance to immune checkpoint blockade in urothelial cancer.

genomics↗

bioRxiv2020

Mis-annotated multi nucleotide variants in public cancer genomics datasets can lead to inaccurate mutation calls with significant implications

BackgroundNext generation sequencing is widely used in cancer to profile tumors and detect variants. Most somatic variant callers used in these pipelines identify variants at the lowest possible granularity - single nucleotide variants (SNVs). As a result, multiple adjacent SNVs are called individually instead of as a multi-nucleotide variant (MNV). The problem with this level of granularity is that the amino acid change from the individual SNVs within a codon could be different from the amino acid change based on the MNV that results from combining the SNVs. Most variant annotation tools do not account for this, leading to incorrect conclusions about the downstream effects of the variants. MethodHere, we used Variant Call Files (VCFs) from the TCGA Mutect2 caller, and developed a solution to merge SNVs to MNVs. Our custom script takes the phasing information from the SNV VCFs and based on a gene model, determines if SNVs are at the same codon and need to be merged into a MNV prior to variant annotation. ResultsWe analyzed 10,383 VCFs from TCGA and found 12,141 MNVs that were incorrectly annotated. Strikingly, the analysis of seven commonly mutated genes from 178 studies from cBioPortal revealed that MNVs were consistently missed in 20 of these studies, while they were correctly annotated in 15 more recent studies. The best and most common example of MNVs was found at the BRAF V600 locus, where several public datasets reported separate BRAF V600E and BRAF V600M variants, instead of a single merged V600K variant. ConclusionWhile some datasets merged MNVs correctly, many public datasets have not been corrected for this problem. As a best practice for variant calling, we recommend that MNVs be accounted for in NGS processing pipelines, thus improving analyses on the impact of somatic variants in cancer genomics.

genomics↗

bioRxiv2020

Integrative Molecular Characterization of Sarcomatoid and Rhabdoid Renal Cell Carcinoma Reveals Determinants of Poor Prognosis and Response to Immune Checkpoint Inhibitors

Sarcomatoid and rhabdoid (S/R) renal cell carcinoma (RCC) are highly aggressive tumors with limited molecular and clinical characterization. Emerging evidence suggests immune checkpoint inhibitors (ICI) are particularly effective for these tumors1-3, although the biological basis for this property is largely unknown. Here, we evaluate multiple clinical trial and real-world cohorts of S/R RCC to characterize their molecular features, clinical outcomes, and immunologic characteristics. We find that S/R RCC tumors harbor distinctive molecular features that may account for their aggressive behavior, including BAP1 mutations, CDKN2A deletions, and increased expression of MYC transcriptional programs. We show that these tumors are highly responsive to ICI and that they exhibit an immune-inflamed phenotype characterized by immune activation, increased cytotoxic immune infiltration, upregulation of antigen presentation machinery genes, and PD-L1 expression. Our findings shed light on the molecular drivers of aggressivity and responsiveness to immune checkpoint inhibitors of S/R RCC tumors.

cancer biology↗