Despite significant benefit for other cancer subtypes, immune checkpoint blockade (ICB) therapy has not yet been shown to significantly improve outcomes for men with castration-resistant prostate ...cancer (CRPC). Prior data have shown that DNA damage response (DDR) deficiency, via genetic alteration and/or pharmacologic induction using DDR inhibitors (DDRi), may improve ICB response in solid tumors in part due to induction of mitotic catastrophe and innate immune activation. Discerning the underlying mechanisms of this DDRi-ICB interaction in a prostate cancer-specific manner is vital to guide novel clinical trials and provide durable clinical responses for men with CRPC.
We treated prostate cancer cell lines with potent, specific inhibitors of ATR kinase, as well as with PARP inhibitor, olaparib. We performed analyses of cGAS-STING and DDR signaling in treated cells, and treated a syngeneic androgen-indifferent, prostate cancer model with combined ATR inhibition and anti-programmed death ligand 1 (anti-PD-L1), and performed single-cell RNA sequencing analysis in treated tumors.
ATR inhibitor (ATRi; BAY1895433) directly repressed ATR-CHK1 signaling, activated CDK1-SPOP axis, leading to destabilization of PD-L1 protein. These effects of ATRi are distinct from those of olaparib, and resulted in a cGAS-STING-initiated, IFN-β-mediated, autocrine, apoptotic response in CRPC. The combination of ATRi with anti-PD-L1 therapy resulted in robust innate immune activation and a synergistic, T-cell-dependent therapeutic response in our syngeneic mouse model.
This work provides a molecular mechanistic rationale for combining ATR-targeted agents with immune checkpoint blockade for patients with CRPC. Multiple early-phase clinical trials of this combination are underway.
Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumours. Therefore, direct study of the functional proteome has the potential to provide a wealth of ...information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cancer Genome Atlas (TCGA) projects. Here we use reverse-phase protein arrays to analyse 3,467 patient samples from 11 TCGA 'Pan-Cancer' diseases, using 181 high-quality antibodies that target 128 total proteins and 53 post-translationally modified proteins. The resultant proteomic data are integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumour lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumour lineages. This integrative analysis, with an emphasis on pathways and potentially actionable proteins, provides a framework for determining the prognostic, predictive and therapeutic relevance of the functional proteome.
Advances in prostate cancer lag behind other tumor types partly due to the paucity of models reflecting key milestones in prostate cancer progression. Therefore, we develop clinically relevant ...prostate cancer models.
Since 1996, we have generated clinically annotated patient-derived xenografts (PDXs; the MDA PCa PDX series) linked to specific phenotypes reflecting all aspects of clinical prostate cancer.
We studied two cell line-derived xenografts and the first 80 PDXs derived from 47 human prostate cancer donors. Of these, 47 PDXs derived from 22 donors are working models and can be expanded either as cell lines (MDA PCa 2a and 2b) or PDXs. The histopathologic, genomic, and molecular characteristics (androgen receptor, ERG, and
loss) maintain fidelity with the human tumor and correlate with published findings. PDX growth response to mouse castration and targeted therapy illustrate their clinical utility. Comparative genomic hybridization and sequencing show significant differences in oncogenic pathways in pairs of PDXs derived from different areas of the same tumor. We also identified a recurrent focal deletion in an area that includes the speckle-type POZ protein-like (
) gene in PDXs derived from seven human donors of 28 studied (25%).
is a
paralog, and
mutations define a molecular subclass of prostate cancer.
deletions are found in 7% of The Cancer Genome Atlas prostate cancers, which suggests that our cohort is a reliable platform for targeted drug development.
The MDA PCa PDX series is a dynamic resource that captures the molecular landscape of prostate cancers progressing under novel treatments and enables optimization of prostate cancer-specific, marker-driven therapy.
We present the genome-wide chromatin accessibility profiles of 410 tumor samples spanning 23 cancer types from The Cancer Genome Atlas (TCGA). We identify 562,709 transposase-accessible DNA elements ...that substantially extend the compendium of known cis-regulatory elements. Integration of ATAC-seq (the assay for transposase-accessible chromatin using sequencing) with TCGA multi-omic data identifies a large number of putative distal enhancers that distinguish molecular subtypes of cancers, uncovers specific driving transcription factors via protein-DNA footprints, and nominates long-range gene-regulatory interactions in cancer. These data reveal genetic risk loci of cancer predisposition as active DNA regulatory elements in cancer, identify gene-regulatory interactions underlying cancer immune evasion, and pinpoint noncoding mutations that drive enhancer activation and may affect patient survival. These results suggest a systematic approach to understanding the noncoding genome in cancer to advance diagnosis and therapy.
Urothelial carcinoma of the bladder is a common malignancy that causes approximately 150,000 deaths per year worldwide. So far, no molecularly targeted agents have been approved for treatment of the ...disease. As part of The Cancer Genome Atlas project, we report here an integrated analysis of 131 urothelial carcinomas to provide a comprehensive landscape of molecular alterations. There were statistically significant recurrent mutations in 32 genes, including multiple genes involved in cell-cycle regulation, chromatin regulation, and kinase signalling pathways, as well as 9 genes not previously reported as significantly mutated in any cancer. RNA sequencing revealed four expression subtypes, two of which (papillary-like and basal/squamous-like) were also evident in microRNA sequencing and protein data. Whole-genome and RNA sequencing identified recurrent in-frame activating FGFR3-TACC3 fusions and expression or integration of several viruses (including HPV16) that are associated with gene inactivation. Our analyses identified potential therapeutic targets in 69% of the tumours, including 42% with targets in the phosphatidylinositol-3-OH kinase/AKT/mTOR pathway and 45% with targets (including ERBB2) in the RTK/MAPK pathway. Chromatin regulatory genes were more frequently mutated in urothelial carcinoma than in any other common cancer studied so far, indicating the future possibility of targeted therapy for chromatin abnormalities.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Consensus molecular subtyping (CMS) of colorectal cancer has potential to reshape the colorectal cancer landscape. We developed and validated an assay that is applicable on formalin-fixed, ...paraffin-embedded (FFPE) samples of colorectal cancer and implemented the assay in a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory.
We performed an
experiment to build an optimal CMS classifier using a training set of 1,329 samples from 12 studies and validation set of 1,329 samples from 14 studies. We constructed an assay on the basis of NanoString CodeSets for the top 472 genes, and performed analyses on paired flash-frozen (FF)/FFPE samples from 175 colorectal cancers to adapt the classifier to FFPE samples using a subset of genes found to be concordant between FF and FFPE, tested the classifier's reproducibility and repeatability, and validated in a CLIA-certified laboratory. We assessed prognostic significance of CMS in 345 patients pooled across three clinical trials.
The best classifier was weighted support vector machine with high accuracy across platforms and gene lists (>0.95), and the 472-gene model outperforming existing classifiers. We constructed subsets of 99 and 200 genes with high FF/FFPE concordance, and adapted FFPE-based classifier that had strong classification accuracy (>80%) relative to "gold standard" CMS. The classifier was reproducible to sample type and RNA quality, and demonstrated poor prognosis for CMS1-3 and good prognosis for CMS2 in metastatic colorectal cancer (
< 0.001).
We developed and validated a colorectal cancer CMS assay that is ready for use in clinical trials, to assess prognosis in standard-of-care settings and explore as predictor of therapy response.
Purpose of Review
This review seeks to provide an informed prospective on the advances in molecular profiling and analysis of colorectal cancer (CRC). The goal is to provide a historical context and ...current summary on how advances in gene and protein sequencing technology along with computer capabilities led to our current bioinformatic advances in the field.
Recent Findings
An explosion of knowledge has occurred regarding genetic, epigenetic, and biochemical alterations associated with the evolution of colorectal cancer. This has led to the realization that CRC is a heterogeneous disease with molecular alterations often dictating natural history, response to treatment, and outcome. The consensus molecular subtypes (CMS) classification classifies CRC into four molecular subtypes with distinct biological characteristics, which may form the basis for clinical stratification and subtype-based targeted intervention.
Summary
This review summarizes new developments of a field moving “Back to the Future.” CRC molecular subtyping will better identify key subtype specific therapeutic targets and responses to therapy.
Cancers with loss-of-function mutations in
or
are deficient in the DNA damage repair pathway called homologous recombination (HR), rendering these cancers exquisitely vulnerable to poly(ADP-ribose) ...polymerase (PARP) inhibitors. This functional state and therapeutic sensitivity is referred to as "BRCAness" and is most commonly associated with some breast cancer types. Pharmaceutical induction of BRCAness could expand the use of PARP inhibitors to other tumor types. For example,
mutations are present in only ~20% of prostate cancer patients. We found that castration-resistant prostate cancer (CRPC) cells showed increased expression of a set of HR-associated genes, including
,
, and
Although androgen-targeted therapy is typically not effective in CRPC patients, the androgen receptor inhibitor enzalutamide suppressed the expression of those HR genes in CRPC cells, thus creating HR deficiency and BRCAness. A "lead-in" treatment strategy, in which enzalutamide was followed by the PARP inhibitor olaparib, promoted DNA damage-induced cell death and inhibited clonal proliferation of prostate cancer cells in culture and suppressed the growth of prostate cancer xenografts in mice. Thus, antiandrogen and PARP inhibitor combination therapy may be effective for CRPC patients and suggests that pharmaceutically inducing BRCAness may expand the clinical use of PARP inhibitors.
Analyzing data from multi-platform genomics experiments combined with patients' clinical outcomes helps us understand the complex biological processes that characterize a disease, as well as how ...these processes relate to the development of the disease. Current data integration approaches are limited in that they do not consider the fundamental biological relationships that exist among the data obtained from different platforms. Statistical Model: We propose an integrative Bayesian analysis of genomics data (iBAG) framework for identifying important genes/biomarkers that are associated with clinical outcome. This framework uses hierarchical modeling to combine the data obtained from multiple platforms into one model.
We assess the performance of our methods using several synthetic and real examples. Simulations show our integrative methods to have higher power to detect disease-related genes than non-integrative methods. Using the Cancer Genome Atlas glioblastoma dataset, we apply the iBAG model to integrate gene expression and methylation data to study their associations with patient survival. Our proposed method discovers multiple methylation-regulated genes that are related to patient survival, most of which have important biological functions in other diseases but have not been previously studied in glioblastoma.
http://odin.mdacc.tmc.edu/∼vbaladan/.
veera@mdanderson.org
Supplementary data are available at Bioinformatics online.
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