Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease

Integrative omics analyses broaden treatment targets in human cancer

Abstract Background Although large-scale, next-generation sequencing (NGS) studies of cancers hold promise for enabling precision oncology, challenges remain in integrating NGS with clinically validated biomarkers. Methods To overcome such challenges, we utilized the Database of Evidence for Precision Oncology (DEPO) to link druggability to genomic, transcriptomic, and proteomic biomarkers. Using a pan-cancer cohort of 6570 tumors, we identified tumors with potentially druggable biomarkers consisting of drug-associated mutations, mRNA expression outliers, and protein/phosphoprotein expression outliers identified by DEPO. Results Within the pan-cancer cohort of 6570 tumors, we found that 3% are druggable based on FDA-approved drug-mutation interactions in specific cancer types. However, mRNA/phosphoprotein/protein expression outliers and drug repurposing across cancer types suggest potential druggability in up to 16% of tumors. The percentage of potential drug-associated tumors can increase to 48% if we consider preclinical evidence. Further, our analyses showed co-occurring potentially druggable multi-omics alterations in 32% of tumors, indicating a role for individualized combinational therapy, with evidence supporting mTOR/PI3K/ESR1 co-inhibition and BRAF/AKT co-inhibition in 1.6 and 0.8% of tumors, respectively. We experimentally validated a subset of putative druggable mutations in BRAF identified by a protein structure-based computational tool. Finally, analysis of a large-scale drug screening dataset lent further evidence supporting repurposing of drugs across cancer types and the use of expression outliers for inferring druggability. Conclusions Our results suggest that an integrated analysis platform can nominate multi-omics alterations as biomarkers of druggability and aid ongoing efforts to bring precision oncology to patients

Systematic Analysis of Splice-Site-Creating Mutations in Cancer.

For the past decade, cancer genomic studies have focused on mutations leading to splice-site disruption, overlooking those having splice-creating potential. Here, we applied a bioinformatic tool, MiSplice, for the large-scale discovery of splice-site-creating mutations (SCMs) across 8,656 TCGA tumors. We report 1,964 originally mis-annotated mutations having clear evidence of creating alternative splice junctions. TP53 and GATA3 have 26 and 18 SCMs, respectively, and ATRX has 5 from lower-grade gliomas. Mutations in 11 genes, including PARP1, BRCA1, and BAP1, were experimentally validated for splice-site-creating function. Notably, we found that neoantigens induced by SCMs are likely several folds more immunogenic compared to missense mutations, exemplified by the recurrent GATA3 SCM. Further, high expression of PD-1 and PD-L1 was observed in tumors with SCMs, suggesting candidates for immune blockade therapy. Our work highlights the importance of integrating DNA and RNA data for understanding the functional and the clinical implications of mutations in human diseases

Additional file 3: of Integrative omics analyses broaden treatment targets in human cancer

Figure S1. Fusions in the TCGA cohort. Figure S2. Druggable protein expression outliers using mass spectrometry. Figure S3. Co-occurring druggable mutations represent opportunities for combinational and alternative therapy. Figure S4. Druggability and Demographics. Figure S5. Potential Druggability by Cancer Type. (PDF 514 KB) (PDF 501 kb

Additional file 1: of Integrative omics analyses broaden treatment targets in human cancer

Supplementary Materials and Methods. (PDF 33 kb

Additional file 2: of Integrative omics analyses broaden treatment targets in human cancer

Table S1. Drug classes in DEPO (database of evidence for precision oncology). Table S2. Sensitive druggable mutations in 6570 TCGA tumors. Table S3. Highest level of evidence present per variant for both resistant and sensitive. Table S4. Drugs represented in the GDSC Cell Line Data. Table S5. Cell lines that contain a sensitive mutation in DEPO. Table S6. Mann-Whitney U test of distribution of Ln(IC50) values in cell lines with DEPO sensitive mutations against background distribution for each drug. Table S7. Linear regression statistics for probe-drug pairs. Table S8. TCGA tumors (out of 3121) that are druggable based on two or more variant types (genomic, transcriptomic, proteomic). Table S9. Ten FDA-approved drug classes. Table S10. TCGA tumors that are druggable with one of ten classes of FDA-approved cancer drugs based on two or more variant types (genomic, transcriptomic, proteomic). Table S11. Druggability and demographics. Table S12. Cancer types responsible for the levels of evidence in the cancer type non-specific setting for Fig. 2a. Table S13. Novel druggable mutations clustering with known druggable mutations identified using HotSpot3D, a proximity-based clustering tool. Table S14. RNA-seq data and protein RPPA data for 6366 and 3877 TCGA tumors, respectively. Table S15. Druggable fusions in TCGA samples. Table S16. Evidence to support repurposing of proteogenomic alterations across cancer types. Table S17. Co-occurring druggable mutations. Table S18. Gene expression outlier scores and drug response for all cell lines. Table S19. TCGA tumors (out of 6570) that are druggable based on atleast one variant (genomic, transcriptomic, proteomic). (.xlsx 2.1 MB) (XLSX 2039 kb

Systematic Analysis of Splice-Site-Creating Mutations in Cancer

© 2018 The Authors For the past decade, cancer genomic studies have focused on mutations leading to splice-site disruption, overlooking those having splice-creating potential. Here, we applied a bioinformatic tool, MiSplice, for the large-scale discovery of splice-site-creating mutations (SCMs) across 8,656 TCGA tumors. We report 1,964 originally mis-annotated mutations having clear evidence of creating alternative splice junctions. TP53 and GATA3 have 26 and 18 SCMs, respectively, and ATRX has 5 from lower-grade gliomas. Mutations in 11 genes, including PARP1, BRCA1, and BAP1, were experimentally validated for splice-site-creating function. Notably, we found that neoantigens induced by SCMs are likely several folds more immunogenic compared to missense mutations, exemplified by the recurrent GATA3 SCM. Further, high expression of PD-1 and PD-L1 was observed in tumors with SCMs, suggesting candidates for immune blockade therapy. Our work highlights the importance of integrating DNA and RNA data for understanding the functional and the clinical implications of mutations in human diseases. Jayasinghe et al. identify nearly 2,000 splice-site-creating mutations (SCMs) from over 8,000 tumor samples across 33 cancer types. They provide a more accurate interpretation of previously mis-annotated mutations, highlighting the importance of integrating data types to understand the functional and the clinical implications of splicing mutations in human disease

Systematic Analysis of Splice-Site-Creating Mutations in Cancer

For the past decade, cancer genomic studies have focused on mutations leading to splice-site disruption, overlooking those having splice-creating potential. Here, we applied a bioinformatic tool, MiSplice, for the large-scale discovery of splice-site-creating mutations (SCMs) across 8,656 TCGA tumors. We report 1,964 originally mis-annotated mutations having clear evidence of creating alternative splice junctions. TP53 and GATA3 have 26 and 18 SCMs, respectively, and ATRX has 5 from lower-grade gliomas. Mutations in 11 genes, including PARP1, BRCA1, and BAP1, were experimentally validated for splice-site-creating function. Notably, we found that neoantigens induced by SCMs are likely several folds more immunogenic compared to missense mutations, exemplified by the recurrent GATA3 SCM. Further, high expression of PD-1 and PD-L1 was observed in tumors with SCMs, suggesting candidates for immune blockade therapy. Our work highlights the importance of integrating DNA and RNA data for understanding the functional and the clinical implications of mutations in human diseases. Jayasinghe et al. identify nearly 2,000 splice-site-creating mutations (SCMs) from over 8,000 tumor samples across 33 cancer types. They provide a more accurate interpretation of previously mis-annotated mutations, highlighting the importance of integrating data types to understand the functional and the clinical implications of splicing mutations in human disease

Systematic Analysis of Splice-Site-Creating Mutations in Cancer

For the past decade, cancer genomic studies have focused on mutations leading to splice-site disruption, overlooking those having splice-creating potential. Here, we applied a bioinformatic tool, MiSplice, for the large-scale discovery of splice-site-creating mutations (SCMs) across 8,656 TCGA tumors. We report 1,964 originally mis-annotated mutations having clear evidence of creating alternative splice junctions. TP53 and GATA3 have 26 and 18 SCMs, respectively, and ATRX has 5 from lower-grade gliomas. Mutations in 11 genes, including PARP1, BRCA1, and BAP1, were experimentally validated for splice-site-creating function. Notably, we found that neoantigens induced by SCMs are likely several folds more immunogenic compared to missense mutations, exemplified by the recurrent GATA3 SCM. Further, high expression of PD-1 and PD-L1 was observed in tumors with SCMs, suggesting candidates for immune blockade therapy. Our work highlights the importance of integrating DNA and RNA data for understanding the functional and the clinical implications of mutations in human diseases. Jayasinghe et al. identify nearly 2,000 splice-site-creating mutations (SCMs) from over 8,000 tumor samples across 33 cancer types. They provide a more accurate interpretation of previously mis-annotated mutations, highlighting the importance of integrating data types to understand the functional and the clinical implications of splicing mutations in human disease