Multi-resolution deep learning characterizes tertiary lymphoid structures and their prognostic relevance in solid tumors.

BACKGROUND: Tertiary lymphoid structures (TLSs) are dense accumulations of lymphocytes in inflamed peripheral tissues, including cancer, and are associated with improved survival and response to immunotherapy in various solid tumors. Histological TLS quantification has been proposed as a novel predictive and prognostic biomarker, but lack of standardized methods of TLS characterization hampers assessment of TLS densities across different patients, diseases, and clinical centers. METHODS: We introduce an approach based on HookNet-TLS, a multi-resolution deep learning model, for automated and unbiased TLS quantification and identification of germinal centers in routine hematoxylin and eosin stained digital pathology slides. We developed HookNet-TLS using n = 1019 manually annotated TCGA slides from clear cell renal cell carcinoma, muscle-invasive bladder cancer, and lung squamous cell carcinoma. RESULTS: Here we show that HookNet-TLS automates TLS quantification across multiple cancer types achieving human-level performance and demonstrates prognostic associations similar to visual assessment. CONCLUSIONS: HookNet-TLS has the potential to be used as a tool for objective quantification of TLS in routine H&E digital pathology slides. We make HookNet-TLS publicly available to promote its use in research.

Tertiary lymphoid structures (TLS) are dense accumulations of immune cells within a cancer. They have been associated with patient survival and treatment effectiveness. Quantification of TLS in cancer microscopy images may therefore aid clinical decision-making. However, no consensus for defining TLS in such images exists leading to inconsistent and variable findings across different labs and studies. We developed a computational tool for automated and objective TLS quantification in cancer images. The tool, called HookNet-TLS, integrates information from multiple image resolutions, which resembles the process of how a pathologist would identify these structures using a microscope. HookNet-TLS detected TLS similarly to trained researchers in three different tumor types. We provided access to HookNet-TLS to facilitate its development and use for TLS assessment in clinical decision-making and research into the role of TLS in cancer.

Biallelic ELOC-Inactivated Renal Cell Carcinoma: Molecular Features Supporting Classification as a Distinct Entity.

Approximately 70% of clear cell renal cell carcinoma (ccRCC) is characterized by the biallelic inactivation of von Hippel-Lindau (VHL) on chromosome 3p. ELOC-mutated (Elongin C-mutated) renal cell carcinoma containing biallelic ELOC inactivations with chromosome 8q deletions is considered a novel subtype of renal cancer possessing a morphologic overlap with ccRCC, renal cell carcinoma (RCC) with fibromyomatous stroma exhibiting Tuberous Sclerosis Complex (TSC)/mammalian Target of Rapamycin (mTOR) mutations, and clear cell papillary tumor. However, the frequency and consequences of ELOC alterations in wild-type VHL and mutated VHL RCC are unclear. In this study, we characterize 123 renal tumors with clear cell morphology and known VHL mutation status to assess the morphologic and molecular consequences of ELOC inactivation. Using OncoScan and whole-exome sequencing, we identify 18 ELOC-deleted RCCs, 3 of which contain ELOC mutations resulting in the biallelic inactivation of ELOC. Biallelic ELOC and biallelic VHL aberrations were mutually exclusive; however, 2 ELOC-mutated RCCs showed monoallelic VHL alterations. Furthermore, no mutations in TSC1, TSC2, or mTOR were identified in ELOC-mutated RCC with biallelic ELOC inactivation. Using High Ambiguity Driven biomolecular DOCKing, we report a novel ELOC variant containing a duplication event disrupting ELOC-VHL interaction alongside the frequently seen Y79C alteration. Using hyper reaction monitoring mass spectrometry, we show RCCs with biallelic ELOC alterations have significantly reduced ELOC expression but similar carbonic anhydrase 9 and vascular endothelial growth factor A expression compared with classical ccRCC with biallelic VHL inactivation. The absence of biallelic VHL and TSC1, TSC2, or mTOR inactivation in RCC with biallelic ELOC inactivation (ELOC mutation in combination with ELOC deletions on chromosome 8q) supports the notion of a novel, molecularly defined tumor entity.

Ex Vivo Drug Testing in Patient-derived Papillary Renal Cancer Cells Reveals EGFR and the BCL2 Family as Therapeutic Targets.

BACKGROUND: Immune checkpoint inhibitors and antiangiogenic agents are used for first-line treatment of advanced papillary renal cell carcinoma (pRCC) but pRCC response rates to these therapies are low. OBJECTIVE: To generate and characterise a functional ex vivo model to identify novel treatment options in advanced pRCC. DESIGN, SETTING, AND PARTICIPANTS: We established patient-derived cell cultures (PDCs) from seven pRCC samples from patients and characterised them via genomic analysis and drug profiling. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Comprehensive molecular characterisation in terms of copy number analysis and whole-exome sequencing confirmed the concordance of pRCC PDCs with the original tumours. We evaluated their sensitivity to novel drugs by generating drug scores for each PDC. RESULTS AND LIMITATIONS: PDCs confirmed pRCC-specific copy number variations such as gains in chromosomes 7, 16, and 17. Whole-exome sequencing revealed that PDCs retained mutations in pRCC-specific driver genes. We performed drug screening with 526 novel and oncological compounds. Whereas exposure to conventional drugs showed low efficacy, the results highlighted EGFR and BCL2 family inhibition as the most effective targets in our pRCC PDCs. CONCLUSIONS: High-throughput drug testing on newly established pRCC PDCs revealed that inhibition of EGFR and BCL2 family members could be a therapeutic strategy in pRCC. PATIENT SUMMARY: We used a new approach to generate patient-derived cells from a specific type of kidney cancer. We showed that these cells have the same genetic background as the original tumour and can be used as models to study novel treatment options for this type of kidney cancer.

Multiplex imaging of breast cancer lymph node metastases identifies prognostic single-cell populations independent of clinical classifiers.

Although breast cancer mortality is largely caused by metastasis, clinical decisions are based on analysis of the primary tumor and on lymph node involvement but not on the phenotype of disseminated cells. Here, we use multiplex imaging mass cytometry to compare single-cell phenotypes of primary breast tumors and matched lymph node metastases in 205 patients. We observe extensive phenotypic variability between primary and metastatic sites and that disseminated cell phenotypes frequently deviate from the clinical disease subtype. We identify single-cell phenotypes and spatial organizations of disseminated tumor cells that are associated with patient survival and a weaker survival association for high-risk phenotypes in the primary tumor. We show that p53 and GATA3 in lymph node metastases provide prognostic information beyond clinical classifiers and can be measured with standard methods. Molecular characterization of disseminated tumor cells is an untapped source of clinically applicable prognostic information for breast cancer.

Altered cytoplasmic and nuclear ADP-ribosylation levels analyzed with an improved ADP-ribose binder are a prognostic factor in renal cell carcinoma.

ADP-ribosylation (ADPR) of proteins is catalyzed by ADP-ribosyltransferases, which are targeted by inhibitors (i.e. poly(ADP-ribose) polymerase inhibitors [PARPi]). Although renal cell carcinoma (RCC) cells are sensitive in vitro to PARPi, studies on the association between ADPR levels and somatic loss of function mutations in DNA damage repair genes are currently missing. Here we observed, in two clear cell RCC (ccRCC) patient cohorts (n = 257 and n = 241) stained with an engineered ADP-ribose binding macrodomain (eAf1521), that decreased cytoplasmic ADPR (cyADPR) levels significantly correlated with late tumor stage, high-ISUP (the International Society of Urological Pathology) grade, presence of necrosis, dense lymphocyte infiltration, and worse patient survival (p < 0.01 each). cyADPR proved to be an independent prognostic factor (p = 0.001). Comparably, absence of nuclear ADPR staining in ccRCC correlated with absence of PARP1 staining (p < 0.01) and worse patient outcome (p < 0.05). In papillary RCC the absence of cyADPR was also significantly associated with tumor progression and worse patient outcome (p < 0.05 each). To interrogate whether the ADPR status could be associated with genetic alterations in DNA repair, chromatin remodeling, and histone modulation, we performed DNA sequence analysis and identified a significant association of increased ARID1A mutations in ccRCCcyADPR+++/PARP1+ compared with ccRCCcyADPR-/PARP1- (31% versus 4%; p < 0.05). Collectively, our data suggest the prognostic value of nuclear and cytoplasmic ADPR levels in RCC that might be further influenced by genetic alterations.

Analysis of the PARP1, ADP-Ribosylation, and TRIP12 Triad With Markers of Patient Outcome in Human Breast Cancer.

PARP inhibitors (PARPi) are increasingly used in breast cancer therapy, including high-grade triple-negative breast cancer (TNBC) treatment. Varying treatment responses and PARPi resistance with relapse currently pose limitations to the efficacy of PARPi therapy. The pathobiological reasons why individual patients respond differently to PARPi are poorly understood. In this study, we analyzed expression of PARP1, the main target of PARPi, in normal breast tissue, breast cancer, and its precursor lesions using human breast cancer tissue microarrays covering a total of 824 patients, including more than 100 TNBC cases. In parallel, we analyzed nuclear adenosine diphosphate (ADP)-ribosylation as a marker of PARP1 activity and TRIP12, an antagonist of PARPi-induced PARP1 trapping. Although we found PARP1 expression to be generally increased in invasive breast cancer, PARP1 protein levels and nuclear ADP-ribosylation were lower in higher tumor grade and TNBC samples than non-TNBCs. Cancers with low levels of PARP1 and low levels of nuclear ADP-ribosylation were associated with significantly reduced overall survival. This effect was even more pronounced in cases with high levels of TRIP12. These results indicate that PARP1-dependent DNA repair capacity may be compromised in aggressive breast cancers, potentially fueling enhanced accumulation of mutations. Moreover, the results revealed a subset of breast cancers with low PARP1, low nuclear ADP-ribosylation, and high TRIP12 levels, which may compromise their response to PARPi, suggesting a combination of markers for PARP1 abundance, enzymatic activity, and trapping capabilities might aid patient stratification for PARPi therapy.

Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging: Diagnostic Pathways and Metabolites for Renal Tumor Entities.

BACKGROUND: Correct tumor subtyping of primary renal tumors is essential for treatment decision in daily routine. Most of the tumors can be classified based on morphology alone. Nevertheless, some diagnoses are difficult, and further investigations are needed for correct tumor subtyping. Besides histochemical investigations, high-mass-resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can detect new diagnostic biomarkers and hence improve the diagnostic. PATIENTS AND METHODS: Formalin-fixed paraffin embedded tissue specimens from clear cell renal cell carcinoma (ccRCC, n = 552), papillary renal cell carcinoma (pRCC, n = 122), chromophobe renal cell carcinoma (chRCC, n = 108), and renal oncocytoma (rO, n = 71) were analyzed by high-mass-resolution MALDI fourier-transform ion cyclotron resonance (FT-ICR) MSI. The SPACiAL pipeline was executed for automated co-registration of histological and molecular features. Pathway enrichment and pathway topology analysis were performed to determine significant differences between RCC subtypes. RESULTS: We discriminated the four histological subtypes (ccRCC, pRCC, chRCC, and rO) and established the subtype-specific pathways and metabolic profiles. rO showed an enrichment of pentose phosphate, taurine and hypotaurine, glycerophospholipid, amino sugar and nucleotide sugar, fructose and mannose, glycine, serine, and threonine pathways. ChRCC is defined by enriched pathways including the amino sugar and nucleotide sugar, fructose and mannose, glycerophospholipid, taurine and hypotaurine, glycine, serine, and threonine pathways. Pyrimidine, amino sugar and nucleotide sugar, glycerophospholipids, and glutathione pathways are enriched in ccRCC. Furthermore, we detected enriched phosphatidylinositol and glycerophospholipid pathways in pRCC. CONCLUSION: In summary, we performed a classification system with a mean accuracy in tumor discrimination of 85.13%. Furthermore, we detected tumor-specific biomarkers for the four most common primary renal tumors by MALDI-MSI. This method is a useful tool in differential diagnosis and biomarker detection.

Next Generation Sequencing of Reactive Stroma and Residual Breast Cancer Cells in Tumor Bed after Neoadjuvant Chemotherapy.

Primary systemic or neoadjuvant chemotherapy of breast cancer has become a standard therapy option in locally advanced or predefined intrinsic subtypes such as triple negative or Her2 positive breast cancer. Neoadjuvant chemotherapy can result in complete pathological response without residual tumor cells (tumor bed) or partial response and non-response with different amounts of reactive stroma and residual tumor cells. The interaction between therapy regimens and tumoral driver mutations have been extensively studied, although the reactive stroma of the tumor bed received less attention. In this study, we characterized the mutational status of residual breast cancer cells and reactive tumor stroma devoid of residual tumor cells in partial or non-responders using next generation sequencing. Twenty-one post-therapeutic breast surgical specimens after neoadjuvant chemotherapy underwent pathogenic driver-mutation screening using microdissected residual breast cancer cells and in reactive stroma adjacent to tumor bed areas. In reactive stroma, no mutations could be validated. In residual breast cancer cells, mutations were detected in sixteen of twenty-one cases (76%). In nine of these twenty-one cases (43%), pathogenic driver mutations (PIK3CA, PTEN, TP53, FN1, PLAG1) were identified. Pathogenic driver-mutations are exclusively restricted to residual carcinoma cells and are absent in reactive stroma independently from intrinsic breast cancer subtypes or tumor stage. These data suggest that the absence of pathogenic mutations in a tumor bed without residual tumor cells may have prognostic implications after neoadjuvant chemotherapy.

Pro-Apoptotic and Anti-Invasive Properties Underscore the Tumor-Suppressing Impact of Myoglobin on a Subset of Human Breast Cancer Cells.

The expression of myoglobin (MB), well known as the oxygen storage and transport protein of myocytes, is a novel hallmark of the luminal subtype in breast cancer patients and correlates with better prognosis. The mechanisms by which MB impacts mammary tumorigenesis are hitherto unclear. We aimed to unravel this role by using CRISPR/Cas9 technology to generate MB-deficient clones of MCF7 and SKBR3 breast cancer cell lines and subsequently characterize them by transcriptomics plus molecular and functional analyses. As main findings, loss of MB at normoxia upregulated the expression of cell cyclins and increased cell survival, while it prevented apoptosis in MCF7 cells. Additionally, MB-deficient cells were less sensitive to doxorubicin but not ionizing radiation. Under hypoxia, the loss of MB enhanced the partial epithelial to mesenchymal transition, thus, augmenting the migratory and invasive behavior of cells. Notably, in human invasive mammary ductal carcinoma tissues, MB and apoptotic marker levels were positively correlated. In addition, MB protein expression in invasive ductal carcinomas was associated with a positive prognostic value, independent of the known tumor suppressor p53. In conclusion, we provide multiple lines of evidence that endogenous MB in cancer cells by itself exerts novel tumor-suppressive roles through which it can reduce cancer malignancy.

MALDI Mass Spectrometry Imaging-Prognostic Pathways and Metabolites for Renal Cell Carcinomas.

High mass resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a suitable method for biomarker detection for several tumor entities. Renal cell carcinoma (RCC) is the seventh most common cancer type and accounts for more than 80% of all renal tumors. Prognostic biomarkers for RCC are still missing. Therefore, we analyzed a large, multicenter cohort including the three most common RCC subtypes (clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC)) by MALDI for prognostic biomarker detection. MALDI-Fourier-transform ion cyclotron resonance (FT-ICR)-MSI analysis was performed for renal carcinoma tissue sections from 782 patients. SPACiAL pipeline was integrated for automated co-registration of histological and molecular features. Kaplan-Meier analyses with overall survival as endpoint were executed to determine the metabolic features associated with clinical outcome. We detected several pathways and metabolites with prognostic power for RCC in general and also for different RCC subtypes.

Prospective observational study of the role of the microbiome in BCG responsiveness prediction (SILENT-EMPIRE): a study protocol.

INTRODUCTION: The human microbiota, the community of micro-organisms in different cavities, has been increasingly linked with inflammatory and neoplastic diseases. While investigation into the gut microbiome has been robust, the urinary microbiome has only recently been described. Investigation into the relationship between bladder cancer (BC) and the bladder and the intestinal microbiome may elucidate a pathophysiological relationship between the two. The bladder or the intestinal microbiome or the interplay between both may also act as a non-invasive biomarker for tumour behaviour. While these associations have not yet been fully investigated, urologists have been manipulating the bladder microbiome for treatment of BC for more than 40 years, treating high grade non-muscle invasive BC (NMIBC) with intravesical BCG immunotherapy. Neither the association between the microbiome sampled directly from bladder tissue and the response to BCG-therapy nor the association between response to BCG-therapy with the faecal microbiome has been studied until now. A prognostic tool prior to initiation of BCG-therapy is still needed. METHODS AND ANALYSIS: In patients with NMIBC bladder samples will be collected during surgery (bladder microbiome assessment), faecal samples (microbiome assessment), instrumented urine and blood samples (biobank) will also be taken. We will analyse the microbial community by 16S rDNA gene amplicon sequencing. The difference in alpha diversity (diversity of species within each sample) and beta diversity (change in species diversity) between BCG-candidates will be assessed. Subgroup analysis will be performed which will lead to the development of a clinical prediction model estimating risk of BCG-response. ETHICS AND DISSEMINATION: The study has been approved by the Cantonal Ethics Committee Zurich (2021-01783) and it is being conducted in accordance with the Declaration of Helsinki and Good Clinical Practice. Study results will be disseminated through peer-reviewed journals and national and international scientific conferences. TRIAL REGISTRATION NUMBER: NCT05204199.

Three-dimensional imaging mass cytometry for highly multiplexed molecular and cellular mapping of tissues and the tumor microenvironment.

A holistic understanding of tissue and organ structure and function requires the detection of molecular constituents in their original three-dimensional (3D) context. Imaging mass cytometry (IMC) enables simultaneous detection of up to 40 antigens and transcripts using metal-tagged antibodies but has so far been restricted to two-dimensional imaging. Here we report the development of 3D IMC for multiplexed 3D tissue analysis at single-cell resolution and demonstrate the utility of the technology by analysis of human breast cancer samples. The resulting 3D models reveal cellular and microenvironmental heterogeneity and cell-level tissue organization not detectable in two dimensions. 3D IMC will prove powerful in the study of phenomena occurring in 3D space such as tumor cell invasion and is expected to provide invaluable insights into cellular microenvironments and tissue architecture.

Statistical tests for intra-tumour clonal co-occurrence and exclusivity.

Tumour progression is an evolutionary process in which different clones evolve over time, leading to intra-tumour heterogeneity. Interactions between clones can affect tumour evolution and hence disease progression and treatment outcome. Intra-tumoural pairs of mutations that are overrepresented in a co-occurring or clonally exclusive fashion over a cohort of patient samples may be suggestive of a synergistic effect between the different clones carrying these mutations. We therefore developed a novel statistical testing framework, called GeneAccord, to identify such gene pairs that are altered in distinct subclones of the same tumour. We analysed our framework for calibration and power. By comparing its performance to baseline methods, we demonstrate that to control type I errors, it is essential to account for the evolutionary dependencies among clones. In applying GeneAccord to the single-cell sequencing of a cohort of 123 acute myeloid leukaemia patients, we find 1 clonally co-occurring and 8 clonally exclusive gene pairs. The clonally exclusive pairs mostly involve genes of the key signalling pathways.

Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression.

Comprehensive genomic studies have delineated key driver mutations linked to disease progression for most cancers. However, corresponding transcriptional changes remain largely elusive because of the bias associated with cross-study analysis. Here, we overcome these hurdles and generate a comprehensive prostate cancer transcriptome atlas that describes the roadmap to tumor progression in a qualitative and quantitative manner. Most cancers follow a uniform trajectory characterized by upregulation of polycomb-repressive-complex-2, G2-M checkpoints, and M2 macrophage polarization. Using patient-derived xenograft models, we functionally validate our observations and add single-cell resolution. Thereby, we show that tumor progression occurs through transcriptional adaption rather than a selection of pre-existing cancer cell clusters. Moreover, we determine at the single-cell level how inhibition of EZH2 - the top upregulated gene along the trajectory - reverts tumor progression and macrophage polarization. Finally, a user-friendly web-resource is provided enabling the investigation of dynamic transcriptional perturbations linked to disease progression.

Spatial protein heterogeneity analysis in frozen tissues to evaluate tumor heterogeneity.

A new workflow for protein-based tumor heterogeneity probing in tissues is here presented. Tumor heterogeneity is believed to be key for therapy failure and differences in prognosis in cancer patients. Comprehending tumor heterogeneity, especially at the protein level, is critical for tracking tumor evolution, and showing the presence of different phenotypical variants and their location with respect to tissue architecture. Although a variety of techniques is available for quantifying protein expression, the heterogeneity observed in the tissue is rarely addressed. The proposed method is validated in breast cancer fresh-frozen tissues derived from five patients. Protein expression is quantified on the tissue regions of interest (ROI) with a resolution of up to 100 µm in diameter. High heterogeneity values across the analyzed patients in proteins such as cytokeratin 7, ß-actin and epidermal growth factor receptor (EGFR) using a Shannon entropy analysis are observed. Additionally, ROIs are clustered according to their expression levels, showing their location in the tissue section, and highlighting that similar phenotypical variants are not always located in neighboring regions. Interestingly, a patient with a phenotype related to increased aggressiveness of the tumor presents a unique protein expression pattern. In summary, a workflow for the localized extraction and protein analysis of regions of interest from frozen tissues, enabling the evaluation of tumor heterogeneity at the protein level is presented.

Spatial Distribution of Private Gene Mutations in Clear Cell Renal Cell Carcinoma.

Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and the molecular tumour composition determines the treatment outcome of renal cancer patients. In renal cancer tumourigenesis, in general, different tumour clones evolve over time. We analysed intra-tumour heterogeneity and subclonal mutation patterns in 178 tumour samples obtained from 89 clear cell renal cell carcinoma patients. In an initial discovery phase, whole-exome and transcriptome sequencing data from paired tumour biopsies from 16 ccRCC patients were used to design a gene panel for follow-up analysis. In this second phase, 826 selected genes were targeted at deep coverage in an extended cohort of 89 patients for a detailed analysis of tumour heterogeneity. On average, we found 22 mutations per patient. Pairwise comparison of the two biopsies from the same tumour revealed that on average, 62% of the mutations in a patient were detected in one of the two samples. In addition to commonly mutated genes (VHL, PBRM1, SETD2 and BAP1), frequent subclonal mutations with low variant allele frequency (<10%) were observed in TP53 and in mucin coding genes MUC6, MUC16, and MUC3A. Of the 89 ccRCC tumours, 87 (~98%) harboured private mutations, occurring in only one of the paired tumour samples. Clonally exclusive pathway pairs were identified using the WES data set from 16 ccRCC patients. Our findings imply that shared and private mutations significantly contribute to the complexity of differential gene expression and pathway interaction and might explain the clonal evolution of different molecular renal cancer subgroups. Multi-regional sequencing is central for the identification of subclones within ccRCC.

Mapping Spatial Genetic Landscapes in Tissue Sections through Microscale Integration of Sampling Methodology into Genomic Workflows.

In cancer research, genomic profiles are often extracted from homogenized macrodissections of tissues, with the histological context lost and a large fraction of material underutilized. Pertinently, the spatial genomic landscape provides critical complementary information in deciphering disease heterogeneity and progression. Microscale sampling methods such as microdissection to obtain such information are often destructive to a sizeable fraction of the biopsy sample, thus showing limited multiplexability and adaptability to different assays. A modular microfluidic technology is here implemented to recover cells at the microscale from tumor tissue sections, with minimal disruption of unsampled areas and tailored to interface with genome profiling workflows, which is directed here toward evaluating intratumoral genomic heterogeneity. The integrated workflow-GeneScape-is used to evaluate heterogeneity in a metastatic mammary carcinoma, showing distinct single nucleotide variants and copy number variations in different tumor tissue regions, suggesting the polyclonal origin of the metastasis as well as development driven by multiple location-specific drivers.

Cytoplasmic ADP-ribosylation levels correlate with markers of patient outcome in distinct human cancers.

ADP-ribosylation (ADPR) is a posttranslational modification whose importance in oncology keeps increasing due to frequent use of PARP inhibitors (PARPi) to treat different tumor types. Due to the lack of suitable tools to analyze cellular ADPR levels, ADPR's significance for cancer progression and patient outcome is unclear. In this study, we assessed ADPR levels by immunohistochemistry using a newly developed anti-ADP-ribose (ADPr) antibody, which is able to detect both mono- and poly-ADPR. Tissue microarrays containing brain (n = 103), breast (n = 1108), colon (n = 236), lung (n = 138), ovarian (n = 142), and prostate (n = 328) cancers were used to correlate ADPR staining intensities to clinico-pathological data, including patient overall survival (OS), tumor grade, tumor stage (pT), lymph node status (pN), and the presence of distant metastasis (pM). While nuclear ADPR was detected only in a minority of the samples, cytoplasmic ADPR (cyADPR) staining was observed in most tumor types. Strong cyADPR intensities were significantly associated with better overall survival in invasive ductal breast cancer (p < 0.0001), invasive lobular breast cancer (p < 0.005), and high grade serous ovarian cancer patients (p < 0.01). Furthermore, stronger cytoplasmic ADPR levels significantly correlated with early tumor stage in colorectal and in invasive ductal breast adenocarcinoma (p < 0.0001 and p < 0.01, respectively) and with the absence of regional lymph node metastasis in colorectal adenocarcinoma (p < 0.05). No correlation to cyADPR was found for prostate and lung cancer or brain tumors. In conclusion, our new anti-ADP-ribose antibody revealed heterogeneous ADPR staining patterns with predominant cytoplasmic ADPR staining in most tumor types. Different cyADPR staining patterns could help to better understand variable response rates to PARP inhibitors in the future.

Dual functions of SPOP and ERG dictate androgen therapy responses in prostate cancer.

Driver genes with a mutually exclusive mutation pattern across tumor genomes are thought to have overlapping roles in tumorigenesis. In contrast, we show here that mutually exclusive prostate cancer driver alterations involving the ERG transcription factor and the ubiquitin ligase adaptor SPOP are synthetic sick. At the molecular level, the incompatible cancer pathways are driven by opposing functions in SPOP. ERG upregulates wild type SPOP to dampen androgen receptor (AR) signaling and sustain ERG activity through degradation of the bromodomain histone reader ZMYND11. Conversely, SPOP-mutant tumors stabilize ZMYND11 to repress ERG-function and enable oncogenic androgen receptor signaling. This dichotomy regulates the response to therapeutic interventions in the AR pathway. While mutant SPOP renders tumor cells susceptible to androgen deprivation therapies, ERG promotes sensitivity to high-dose androgen therapy and pharmacological inhibition of wild type SPOP. More generally, these results define a distinct class of antagonistic cancer drivers and a blueprint toward their therapeutic exploitation.