Distinct Classes of Complex Structural Variation Uncovered across Thousands of Cancer Genome Graphs.

Cancer genomes often harbor hundreds of somatic DNA rearrangement junctions, many of which cannot be easily classified into simple (e.g., deletion) or complex (e.g., chromothripsis) structural variant classes. Applying a novel genome graph computational paradigm to analyze the topology of junction copy number (JCN) across 2,778 tumor whole-genome sequences, we uncovered three novel complex rearrangement phenomena: pyrgo, rigma, and tyfonas. Pyrgo are "towers" of low-JCN duplications associated with early-replicating regions, superenhancers, and breast or ovarian cancers. Rigma comprise "chasms" of low-JCN deletions enriched in late-replicating fragile sites and gastrointestinal carcinomas. Tyfonas are "typhoons" of high-JCN junctions and fold-back inversions associated with expressed protein-coding fusions, breakend hypermutation, and acral, but not cutaneous, melanomas. Clustering of tumors according to genome graph-derived features identified subgroups associated with DNA repair defects and poor prognosis.

Organoid cultures derived from patients with advanced prostate cancer.

The lack of in vitro prostate cancer models that recapitulate the diversity of human prostate cancer has hampered progress in understanding disease pathogenesis and therapy response. Using a 3D organoid system, we report success in long-term culture of prostate cancer from biopsy specimens and circulating tumor cells. The first seven fully characterized organoid lines recapitulate the molecular diversity of prostate cancer subtypes, including TMPRSS2-ERG fusion, SPOP mutation, SPINK1 overexpression, and CHD1 loss. Whole-exome sequencing shows a low mutational burden, consistent with genomics studies, but with mutations in FOXA1 and PIK3R1, as well as in DNA repair and chromatin modifier pathways that have been reported in advanced disease. Loss of p53 and RB tumor suppressor pathway function are the most common feature shared across the organoid lines. The methodology described here should enable the generation of a large repertoire of patient-derived prostate cancer lines amenable to genetic and pharmacologic studies.

Punctuated evolution of prostate cancer genomes.

The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and progression. By modeling the genesis of genomic rearrangements, we identified abundant DNA translocations and deletions that arise in a highly interdependent manner. This phenomenon, which we term "chromoplexy," frequently accounts for the dysregulation of prostate cancer genes and appears to disrupt multiple cancer genes coordinately. Our modeling suggests that chromoplexy may induce considerable genomic derangement over relatively few events in prostate cancer and other neoplasms, supporting a model of punctuated cancer evolution. By characterizing the clonal hierarchy of genomic lesions in prostate tumors, we charted a path of oncogenic events along which chromoplexy may drive prostate carcinogenesis.

Author Correction: FOXA1 mutations alter pioneering activity, differentiation and prostate cancer phenotypes.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

ZFX Mediates Non-canonical Oncogenic Functions of the Androgen Receptor Splice Variant 7 in Castrate-Resistant Prostate Cancer.

Androgen receptor splice variant 7 (AR-V7) is crucial for prostate cancer progression and therapeutic resistance. We show that, independent of ligand, AR-V7 binds both androgen-responsive elements (AREs) and non-canonical sites distinct from full-length AR (AR-FL) targets. Consequently, AR-V7 not only recapitulates AR-FL's partial functions but also regulates an additional gene expression program uniquely via binding to gene promoters rather than ARE enhancers. AR-V7 binding and AR-V7-mediated activation at these unique targets do not require FOXA1 but rely on ZFX and BRD4. Knockdown of ZFX or select unique targets of AR-V7/ZFX, or BRD4 inhibition, suppresses growth of castration-resistant prostate cancer cells. We also define an AR-V7 direct target gene signature that correlates with AR-V7 expression in primary tumors, differentiates metastatic prostate cancer from normal, and predicts poor prognosis. Thus, AR-V7 has both ARE/FOXA1 canonical and ZFX-directed non-canonical regulatory functions in the evolution of anti-androgen therapeutic resistance, providing information to guide effective therapeutic strategies.

Multicenter phase 2 study of oral azacitidine (CC-486) plus CHOP as initial treatment for PTCL.

Peripheral T-cell lymphomas (PTCL) with T-follicular helper phenotype (PTCL-TFH) has recurrent mutations affecting epigenetic regulators, which may contribute to aberrant DNA methylation and chemoresistance. This phase 2 study evaluated oral azacitidine (CC-486) plus cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) as initial treatment for PTCL. CC-486 at 300 mg daily was administered for 7 days before C1 of CHOP, and for 14 days before CHOP C2-6. The primary end point was end-of-treatment complete response (CR). Secondary end points included safety and survival. Correlative studies assessed mutations, gene expression, and methylation in tumor samples. Grade 3 to 4 hematologic toxicities were mostly neutropenia (71%), with febrile neutropenia uncommon (14%). Nonhematologic toxicities included fatigue (14%) and gastrointestinal symptoms (5%). In 20 evaluable patients, CR was 75%, including 88.2% for PTCL-TFH (n = 17). The 2-year progression-free survival (PFS) was 65.8% for all and 69.2% for PTCL-TFH, whereas 2-year overall survival (OS) was 68.4% for all and 76.1% for PTCL-TFH. The frequencies of the TET2, RHOA, DNMT3A, and IDH2 mutations were 76.5%, 41.1%, 23.5%, and 23.5%, respectively, with TET2 mutations significantly associated with CR (P = .007), favorable PFS (P = .004) and OS (P = .015), and DNMT3A mutations associated with adverse PFS (P = .016). CC-486 priming contributed to the reprograming of the tumor microenvironment by upregulation of genes related to apoptosis (P < .01) and inflammation (P < .01). DNA methylation did not show significant shift. This safe and active regimen is being further evaluated in the ALLIANCE randomized study A051902 in CD30-negative PTCL. This trial was registered at www.clinicaltrials.gov as #NCT03542266.

FOXA1 mutations alter pioneering activity, differentiation and prostate cancer phenotypes.

Mutations in the transcription factor FOXA1 define a unique subset of prostate cancers but the functional consequences of these mutations and whether they confer gain or loss of function is unknown1-9. Here, by annotating the landscape of FOXA1 mutations from 3,086 human prostate cancers, we define two hotspots in the forkhead domain: Wing2 (around 50% of all mutations) and the highly conserved DNA-contact residue R219 (around 5% of all mutations). Wing2 mutations are detected in adenocarcinomas at all stages, whereas R219 mutations are enriched in metastatic tumours with neuroendocrine histology. Interrogation of the biological properties of wild-type FOXA1 and fourteen FOXA1 mutants reveals gain of function in mouse prostate organoid proliferation assays. Twelve of these mutants, as well as wild-type FOXA1, promoted an exaggerated pro-luminal differentiation program, whereas two different R219 mutants blocked luminal differentiation and activated a mesenchymal and neuroendocrine transcriptional program. Assay for transposase-accessible chromatin using sequencing (ATAC-seq) of wild-type FOXA1 and representative Wing2 and R219 mutants revealed marked, mutant-specific changes in open chromatin at thousands of genomic loci and exposed sites of FOXA1 binding and associated increases in gene expression. Of note, ATAC-seq peaks in cells expressing R219 mutants lacked the canonical core FOXA1-binding motifs (GTAAAC/T) but were enriched for a related, non-canonical motif (GTAAAG/A), which was preferentially activated by R219-mutant FOXA1 in reporter assays. Thus, FOXA1 mutations alter its pioneering function and perturb normal luminal epithelial differentiation programs, providing further support for the role of lineage plasticity in cancer progression.

Whole-Genome Sequencing Analysis of Male Breast Cancer Unveils Novel Structural Events and Potential Therapeutic Targets.

The molecular characterization of male breast cancer (MaBC) has received limited attention in research, mostly because of its low incidence rate, accounting for only 0.5% to 1% of all reported cases of breast cancer each year. Managing MaBC presents significant challenges, with most treatment protocols being adapted from those developed for female breast cancer. Utilizing whole-genome sequencing (WGS) and state-of-the-art analyses, the genomic features of 10 MaBC cases (n = 10) were delineated and correlated with clinical and histopathologic characteristics. Using fluorescence in situ hybridization, an additional cohort of 18 patients was interrogated to supplement WGS findings. The genomic landscape of MaBC uncovered significant genetic alterations that could influence diagnosis and treatment. We found common somatic mutations in key driver genes, such as FAT1, GATA3, SMARCA4, and ARID2. Our study also mapped out structural variants that impact cancer-associated genes, such as ARID1A, ESR1, GATA3, NTRK1, and NF1. Using a WGS-based classifier, homologous recombination deficiency (HRD) was identified in 2 cases, both presenting with deleterious variants in BRCA2. Noteworthy was the observation of FGFR1 amplification in 21% of cases. Altogether, we identified at least 1 potential therapeutic target in 8 of the 10 cases, including high tumor mutational burden, FGFR1 amplification, and HRD. Our study is the first WGS characterization of MaBC, which uncovered potentially relevant variants, including structural events in cancer genes, HRD signatures, and germline pathogenic mutations. Our results demonstrate unique genetic markers and potential treatment targets in MaBC, thereby underlining the necessity of tailoring treatment strategies for this understudied patient population. These WGS-based findings add to the growing knowledge of MaBC genomics and highlight the need to expand research on this type of cancer.

Suppression of insulin feedback enhances the efficacy of PI3K inhibitors.

Mutations in PIK3CA, which encodes the p110α subunit of the insulin-activated phosphatidylinositol-3 kinase (PI3K), and loss of function mutations in PTEN, which encodes a phosphatase that degrades the phosphoinositide lipids generated by PI3K, are among the most frequent events in human cancers1,2. However, pharmacological inhibition of PI3K has resulted in variable clinical responses, raising the possibility of an inherent mechanism of resistance to treatment. As p110α mediates virtually all cellular responses to insulin, targeted inhibition of this enzyme disrupts glucose metabolism in multiple tissues. For example, blocking insulin signalling promotes glycogen breakdown in the liver and prevents glucose uptake in the skeletal muscle and adipose tissue, resulting in transient hyperglycaemia within a few hours of PI3K inhibition. The effect is usually transient because compensatory insulin release from the pancreas (insulin feedback) restores normal glucose homeostasis3. However, the hyperglycaemia may be exacerbated or prolonged in patients with any degree of insulin resistance and, in these cases, necessitates discontinuation of therapy3-6. We hypothesized that insulin feedback induced by PI3K inhibitors may reactivate the PI3K-mTOR signalling axis in tumours, thereby compromising treatment effectiveness7,8. Here we show, in several model tumours in mice, that systemic glucose-insulin feedback caused by targeted inhibition of this pathway is sufficient to activate PI3K signalling, even in the presence of PI3K inhibitors. This insulin feedback can be prevented using dietary or pharmaceutical approaches, which greatly enhance the efficacy/toxicity ratios of PI3K inhibitors. These findings have direct clinical implications for the multiple p110α inhibitors that are in clinical trials and provide a way to increase treatment efficacy for patients with many types of tumour.

Publisher Correction: Suppression of insulin feedback enhances the efficacy of PI3K inhibitors.

In this Letter, author Xing Du was incorrectly listed as Du Xing; this has been corrected online.

Comparative genomics of primary prostate cancer and paired metastases: insights from 12 molecular case studies.

Primary prostate cancer (PCa) can show marked molecular heterogeneity. However, systematic analyses comparing primary PCa and matched metastases in individual patients are lacking. We aimed to address the molecular aspects of metastatic progression while accounting for the heterogeneity of primary PCa. In this pilot study, we collected 12 radical prostatectomy (RP) specimens from men who subsequently developed metastatic castration-resistant prostate cancer (mCRPC). We used histomorphology (Gleason grade, focus size, stage) and immunohistochemistry (IHC) (ERG and p53) to identify independent tumors and/or distinct subclones of primary PCa. We then compared molecular profiles of these primary PCa areas to matched metastatic samples using whole-exome sequencing (WES) and amplicon-based DNA and RNA sequencing. Based on combined pathology and molecular analysis, seven (58%) RP specimens harbored monoclonal and topographically continuous disease, albeit with some degree of intratumor heterogeneity; four (33%) specimens showed true multifocal disease; and one displayed monoclonal disease with discontinuous topography. Early (truncal) events in primary PCa included SPOP p.F133V (one patient), BRAF p.K601E (one patient), and TMPRSS2:ETS rearrangements (eight patients). Activating AR alterations were seen in nine (75%) mCRPC patients, but not in matched primary PCa. Hotspot TP53 mutations, found in metastases from three patients, were readily present in matched primary disease. Alterations in genes encoding epigenetic modifiers were observed in several patients (either shared between primary foci and metastases or in metastatic samples only). WES-based phylogenetic reconstruction and/or clonality scores were consistent with the index focus designated by pathology review in six out of nine (67%) cases. The three instances of discordance pertained to monoclonal, topographically continuous tumors, which would have been considered as unique disease in routine practice. Overall, our results emphasize pathologic and molecular heterogeneity of primary PCa, and suggest that comprehensive IHC-assisted pathology review and genomic analysis are highly concordant in nominating the 'index' primary PCa area. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Transcriptional and metabolic remodeling in clear cell renal cell carcinoma caused by ATF4 activation and the integrated stress response (ISR).

Research has shown extensive metabolic remodeling in clear cell renal cell carcinoma (ccRCC), with increased glutathione (GSH) levels. We hypothesized that activating transcription factor-4 (ATF4) and the integrated stress response (ISR) induce a metabolic shift, including increased GSH accumulation, and that Vitamin A deficiency (VAD), found in ccRCCs, can also activate ATF4 signaling in the kidney. To determine the role of ATF4, we used publicly available RNA sequencing (RNA-seq) data sets from The Cancer Genomics Atlas. Subsequently, we performed RNA-seq and liquid chromatography-mass spectrometry-based metabolomics analysis of the murine TRAnsgenic Cancer of the Kidney (TRACK) model for early-stage ccRCC. To validate our findings, we generated RCC4 cell lines with ATF4 gene edits (ATF4-knockout [KO]) and subjected these cells to metabolic isotope tracing. Analysis of variance, the two-sided Student's t test, and gene set enrichment analysis were used (p < 0.05) to determine statistical significance. Here we show that most human ccRCC tumors exhibit activation of the transcription factor ATF4. Activation of ATF4 is concomitant with enrichment of the ATF4 gene set and elevated expression of ATF4 target genes ASNS, ALDH1L2, MTHFD2, DDIT3 (CHOP), DDIT4, TRIB3, EIF4EBP1, SLC7A11, and PPP1R15A (GADD34). Transcript profiling and metabolomics analyses show that activated hypoxia-inducible factor-1α (HIF1α) signaling in our TRACK ccRCC murine model also induces an ATF4-mediated ISR. Notably, both normoxic HIF1α signaling in TRACK kidneys and VAD in wild-type kidneys diminish amino acid levels, increase ASNS, TRIB3, and MTHFD2 messenger RNA levels, and increase levels of lipids and GSH. By metabolic isotope tracing in human RCC4 kidney cancer parental and ATF4 gene-edited (ATF4-KO) cell lines, we show that ATF4 increases GSH accumulation in part via activation of the mitochondrial one-carbon metabolism pathway. Our results demonstrate for the first time that activation of ATF4 enhances GSH accumulation, increases purine and pyrimidine biosynthesis, and contributes to transcriptional and metabolic remodeling in ccRCC. Moreover, constitutive HIF1α expressed only in murine kidney proximal tubules activates ATF4, leading to the metabolic changes associated with the ISR. Our data indicate that HIF1α can promote ccRCC via ATF4 activation. Moreover, lack of Vitamin A in the kidney recapitulates aspects of the ISR.

Application of artificial intelligence to overcome clinical information overload in urological cancer.

OBJECTIVE: To describe the use of artificial intelligence (AI) in medical literature and trial data extraction, and its applications in uro-oncology. This bridging review, which consolidates information from the diverse applications of AI, highlights how AI users can investigate more sophisticated queries than with traditional methods, leading to synthesis of raw data and complex outputs into more actionable and personalised results, particularly in the field of uro-oncology. METHODS: Literature and clinical trial searches were performed in PubMed, Dimensions, Embase and Google (1999-2020). The searches focussed on the use of AI and its various forms to facilitate literature searches, clinical guidelines development, and clinical trial data extraction in uro-oncology. To illustrate how AI can be applied to address questions about optimising therapeutic decision making and individualising treatment regimens, the Dimensions-linked information platform was searched for 'prostate cancer' keywords (76 publications were identified; 48 were included). RESULTS: AI offers the promise of transforming raw data and complex outputs into actionable insights. Literature and clinical trial searches can be automated, enabling clinicians to develop and analyse publications expeditiously on complex issues such as therapeutic sequencing and to obtain updates on documents that evolve at the pace and scope of the landscape. An AI-based platform inclusive of 12 trial databases and >100 scientific literature sources enabled the creation of an interactive visualisation. CONCLUSION: As the literature and clinical trial landscape continues to grow in complexity and with increasing speed, the ability to pull the right information at the right time from different search engines and resources, while excluding social media bias, becomes more challenging. This review demonstrates that by applying natural language processing and machine learning algorithms, validated and optimised AI leads to a speedier, more personalised, efficient, and focussed search compared with traditional methods.

Molecular Evaluation of Low-grade Low-stage Endometrial Cancer With and Without Recurrence.

Low-grade, low-stage endometrioid carcinomas (LGLS EC) demonstrate 5-yr survival rates up to 95%. However, a small subset of these tumors recur, and little is known about prognostic markers or established mutation profiles associated with recurrence. The goal of the current study was to identify the molecular profiles of the primary carcinomas and the genomic differences between primary tumors and subsequent recurrences. Four cases of LGLS EC with recurrence and 8 cases without recurrence were evaluated via whole-exome sequencing. Three of the 4 recurrent tumors were evaluated via Oncomine Comprehensive Assay. The resulting molecular profiles of the primary and recurrent tumors were compared. Two of the 3 recurrent cases showed additional mutations in the recurrence. One recurrent tumor included an additional TP53 mutation and the other recurrent tumor showed POLE and DDR2 kinase gene mutation. The POLE mutation occurred outside the exonuclease domain. PIK3CA mutations were detected in 4 of 4 primary LGLS EC with recurrence and in 3 of 8 disease-free cases. LGLS EC with recurrence showed higher MSIsensor scores compared with LGLS without recurrence. The level of copy number gains in LGLS EC with recurrence was larger than LGLS EC without recurrence. This pilot study showed 1 of 3 recurrent cases gained a mutation associated with genetic instability (TP53) and 1 of them also acquired a mutation in the DDR2 kinase, a potential therapeutic target. We also noted a higher level of copy number gains, MSIsensor scores and PIK3CA mutations in the primary tumors that later recurred.

Genomic correlates of clinical outcome in advanced prostate cancer.

Heterogeneity in the genomic landscape of metastatic prostate cancer has become apparent through several comprehensive profiling efforts, but little is known about the impact of this heterogeneity on clinical outcome. Here, we report comprehensive genomic and transcriptomic analysis of 429 patients with metastatic castration-resistant prostate cancer (mCRPC) linked with longitudinal clinical outcomes, integrating findings from whole-exome, transcriptome, and histologic analysis. For 128 patients treated with a first-line next-generation androgen receptor signaling inhibitor (ARSI; abiraterone or enzalutamide), we examined the association of 18 recurrent DNA- and RNA-based genomic alterations, including androgen receptor (AR) variant expression, AR transcriptional output, and neuroendocrine expression signatures, with clinical outcomes. Of these, only RB1 alteration was significantly associated with poor survival, whereas alterations in RB1, AR, and TP53 were associated with shorter time on treatment with an ARSI. This large analysis integrating mCRPC genomics with histology and clinical outcomes identifies RB1 genomic alteration as a potent predictor of poor outcome, and is a community resource for further interrogation of clinical and molecular associations.

Validation of a Circulating Tumor DNA-Based Next-Generation Sequencing Assay in a Cohort of Patients with Solid tumors: A Proposed Solution for Decentralized Plasma Testing.

BACKGROUND: Characterization of circulating tumor DNA (ctDNA) has been integrated into clinical practice. Although labs have standardized validation procedures to develop single locus tests, the efficacy of on-site plasma-based next-generation sequencing (NGS) assays still needs to be proved. MATERIALS AND METHODS: In this retrospective study, we profiled DNA from matched tissue and plasma samples from 75 patients with cancer. We applied an NGS test that detects clinically relevant alterations in 33 genes and microsatellite instability (MSI) to analyze plasma cell-free DNA (cfDNA). RESULTS: The concordance between alterations detected in both tissue and plasma samples was higher in patients with metastatic disease. The NGS test detected 77% of sequence alterations, amplifications, and fusions that were found in metastatic samples compared with 45% of those alterations found in the primary tumor samples (p = .00005). There was 87% agreement on MSI status between the NGS test and tumor tissue results. In three patients, MSI-high ctDNA correlated with response to immunotherapy. In addition, the NGS test revealed an FGFR2 amplification that was not detected in tumor tissue from a patient with metastatic gastric cancer, emphasizing the importance of profiling plasma samples in patients with advanced cancer. CONCLUSION: Our validation experience of a plasma-based NGS assay advances current knowledge about translating cfDNA testing into clinical practice and supports the application of plasma assays in the management of oncology patients with metastatic disease. With an in-house method that minimizes the need for invasive procedures, on-site cfDNA testing supplements tissue biopsy to guide precision therapy and is entitled to become a routine practice. IMPLICATIONS FOR PRACTICE: This study proposes a solution for decentralized liquid biopsy testing based on validation of a next-generation sequencing (NGS) test that detects four classes of genomic alterations in blood: sequence mutations (single nucleotide substitutions or insertions and deletions), fusions, amplifications, and microsatellite instability (MSI). Although there are reference labs that perform single-site comprehensive liquid biopsy testing, the targeted assay this study validated can be established locally in any lab with capacity to offer clinical molecular pathology assays. To the authors' knowledge, this is the first report that validates evaluating an on-site plasma-based NGS test that detects the MSI status along with common sequence alterations encountered in solid tumors.

ABEMUS: platform-specific and data-informed detection of somatic SNVs in cfDNA.

MOTIVATION: The use of liquid biopsies for cancer patients enables the non-invasive tracking of treatment response and tumor dynamics through single or serial blood drawn tests. Next-generation sequencing assays allow for the simultaneous interrogation of extended sets of somatic single-nucleotide variants (SNVs) in circulating cell-free DNA (cfDNA), a mixture of DNA molecules originating both from normal and tumor tissue cells. However, low circulating tumor DNA (ctDNA) fractions together with sequencing background noise and potential tumor heterogeneity challenge the ability to confidently call SNVs. RESULTS: We present a computational methodology, called Adaptive Base Error Model in Ultra-deep Sequencing data (ABEMUS), which combines platform-specific genetic knowledge and empirical signal to readily detect and quantify somatic SNVs in cfDNA. We tested the capability of our method to analyze data generated using different platforms with distinct sequencing error properties and we compared ABEMUS performances with other popular SNV callers on both synthetic and real cancer patients sequencing data. Results show that ABEMUS performs better in most of the tested conditions proving its reliability in calling low variant allele frequencies somatic SNVs in low ctDNA levels plasma samples. AVAILABILITY AND IMPLEMENTATION: ABEMUS is cross-platform and can be installed as R package. The source code is maintained on Github at http://github.com/cibiobcg/abemus, and it is also available at CRAN official R repository. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology-Radiology Fusion.

BACKGROUND: A definitive diagnosis of prostate cancer requires a biopsy to obtain tissue for pathologic analysis, but this is an invasive procedure and is associated with complications. PURPOSE: To develop an artificial intelligence (AI)-based model (named AI-biopsy) for the early diagnosis of prostate cancer using magnetic resonance (MR) images labeled with histopathology information. STUDY TYPE: Retrospective. POPULATION: Magnetic resonance imaging (MRI) data sets from 400 patients with suspected prostate cancer and with histological data (228 acquired in-house and 172 from external publicly available databases). FIELD STRENGTH/SEQUENCE: 1.5 to 3.0 Tesla, T2-weighted image pulse sequences. ASSESSMENT: MR images reviewed and selected by two radiologists (with 6 and 17 years of experience). The patient images were labeled with prostate biopsy including Gleason Score (6 to 10) or Grade Group (1 to 5) and reviewed by one pathologist (with 15 years of experience). Deep learning models were developed to distinguish 1) benign from cancerous tumor and 2) high-risk tumor from low-risk tumor. STATISTICAL TESTS: To evaluate our models, we calculated negative predictive value, positive predictive value, specificity, sensitivity, and accuracy. We also calculated areas under the receiver operating characteristic (ROC) curves (AUCs) and Cohen's kappa. RESULTS: Our computational method (https://github.com/ih-lab/AI-biopsy) achieved AUCs of 0.89 (95% confidence interval [CI]: [0.86-0.92]) and 0.78 (95% CI: [0.74-0.82]) to classify cancer vs. benign and high- vs. low-risk of prostate disease, respectively. DATA CONCLUSION: AI-biopsy provided a data-driven and reproducible way to assess cancer risk from MR images and a personalized strategy to potentially reduce the number of unnecessary biopsies. AI-biopsy highlighted the regions of MR images that contained the predictive features the algorithm used for diagnosis using the class activation map method. It is a fully automatic method with a drag-and-drop web interface (https://ai-biopsy.eipm-research.org) that allows radiologists to review AI-assessed MR images in real time. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

Alternative transcription initiation leads to expression of a novel ALK isoform in cancer.

Activation of oncogenes by mechanisms other than genetic aberrations such as mutations, translocations, or amplifications is largely undefined. Here we report a novel isoform of the anaplastic lymphoma kinase (ALK) that is expressed in ∼11% of melanomas and sporadically in other human cancer types, but not in normal tissues. The novel ALK transcript initiates from a de novo alternative transcription initiation (ATI) site in ALK intron 19, and was termed ALK(ATI). In ALK(ATI)-expressing tumours, the ATI site is enriched for H3K4me3 and RNA polymerase II, chromatin marks characteristic of active transcription initiation sites. ALK(ATI) is expressed from both ALK alleles, and no recurrent genetic aberrations are found at the ALK locus, indicating that the transcriptional activation is independent of genetic aberrations at the ALK locus. The ALK(ATI) transcript encodes three proteins with molecular weights of 61.1, 60.8 and 58.7 kilodaltons, consisting primarily of the intracellular tyrosine kinase domain. ALK(ATI) stimulates multiple oncogenic signalling pathways, drives growth-factor-independent cell proliferation in vitro, and promotes tumorigenesis in vivo in mouse models. ALK inhibitors can suppress the kinase activity of ALK(ATI), suggesting that patients with ALK(ATI)-expressing tumours may benefit from ALK inhibitors. Our findings suggest a novel mechanism of oncogene activation in cancer through de novo alternative transcription initiation.

Oncogenic Addiction to ERBB2 Signaling Predicts Response to Trastuzumab in Urothelial Cancer.

Urothelial carcinoma (UC) is a common and frequently lethal cancer. Despite the presence of genomic alterations creating dependency on particular signaling pathways, the use of targeted therapies in advanced and metastatic UC has been limited. We performed an integrated analysis of whole-exome and RNA sequencing of primary and metastatic tumors in a patient with platinum-resistant UC. We found a strikingly high ERBB2 mRNA expression and enrichment of downstream oncogenic ERBB2 signaling in this patient's tumors compared with tumors from an unselected group of patients with UC (N=17). This patient had an exceptional sustained response to trastuzumab. Our findings show that oncogenic addiction to ERBB2 signaling potentially predicts response to ERBB2-directed therapy of UC.