Pan-cancer analysis of post-translational modifications reveals shared patterns of protein regulation.

Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable high-throughput, accurate, and sensitive measurement of PTM levels to better understand their role, prevalence, and crosstalk. Here, we analyze the largest collection of proteogenomics data from 1,110 patients with PTM profiles across 11 cancer types (10 from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium [CPTAC]). Our study reveals pan-cancer patterns of changes in protein acetylation and phosphorylation involved in hallmark cancer processes. These patterns revealed subsets of tumors, from different cancer types, including those with dysregulated DNA repair driven by phosphorylation, altered metabolic regulation associated with immune response driven by acetylation, affected kinase specificity by crosstalk between acetylation and phosphorylation, and modified histone regulation. Overall, this resource highlights the rich biology governed by PTMs and exposes potential new therapeutic avenues.

Pan-cancer proteogenomics connects oncogenic drivers to functional states.

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma.

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

The Landscape of Circular RNA in Cancer.

Circular RNAs (circRNAs) are an intriguing class of RNA due to their covalently closed structure, high stability, and implicated roles in gene regulation. Here, we used an exome capture RNA sequencing protocol to detect and characterize circRNAs across >2,000 cancer samples. When compared against Ribo-Zero and RNase R, capture sequencing significantly enhanced the enrichment of circRNAs and preserved accurate circular-to-linear ratios. Using capture sequencing, we built the most comprehensive catalog of circRNA species to date: MiOncoCirc, the first database to be composed primarily of circRNAs directly detected in tumor tissues. Using MiOncoCirc, we identified candidate circRNAs to serve as biomarkers for prostate cancer and were able to detect circRNAs in urine. We further detected a novel class of circular transcripts, termed read-through circRNAs, that involved exons originating from different genes. MiOncoCirc will serve as a valuable resource for the development of circRNAs as diagnostic or therapeutic targets across cancer types.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Oncogenic Role of THOR, a Conserved Cancer/Testis Long Non-coding RNA.

Large-scale transcriptome sequencing efforts have vastly expanded the catalog of long non-coding RNAs (lncRNAs) with varying evolutionary conservation, lineage expression, and cancer specificity. Here, we functionally characterize a novel ultraconserved lncRNA, THOR (ENSG00000226856), which exhibits expression exclusively in testis and a broad range of human cancers. THOR knockdown and overexpression in multiple cell lines and animal models alters cell or tumor growth supporting an oncogenic role. We discovered a conserved interaction of THOR with IGF2BP1 and show that THOR contributes to the mRNA stabilization activities of IGF2BP1. Notably, transgenic THOR knockout produced fertilization defects in zebrafish and also conferred a resistance to melanoma onset. Likewise, ectopic expression of human THOR in zebrafish accelerated the onset of melanoma. THOR represents a novel class of functionally important cancer/testis lncRNAs whose structure and function have undergone positive evolutionary selection.

Expressed pseudogenes in the transcriptional landscape of human cancers.

Pseudogene transcripts can provide a novel tier of gene regulation through generation of endogenous siRNAs or miRNA-binding sites. Characterization of pseudogene expression, however, has remained confined to anecdotal observations due to analytical challenges posed by the extremely close sequence similarity with their counterpart coding genes. Here, we describe a systematic analysis of pseudogene "transcription" from an RNA-Seq resource of 293 samples, representing 13 cancer and normal tissue types, and observe a surprisingly prevalent, genome-wide expression of pseudogenes that could be categorized as ubiquitously expressed or lineage and/or cancer specific. Further, we explore disease subtype specificity and functions of selected expressed pseudogenes. Taken together, we provide evidence that transcribed pseudogenes are a significant contributor to the transcriptional landscape of cells and are positioned to play significant roles in cellular differentiation and cancer progression, especially in light of the recently described ceRNA networks. Our work provides a transcriptome resource that enables high-throughput analyses of pseudogene expression.

Expression of L1 Cell Adhesion Molecule (L1CAM), A Nephronal Principal Cell Marker, in Nephrogenic Adenoma.

Nephrogenic adenoma is a benign, reactive lesion seen predominantly in the urinary bladder and often associated with an antecedent inflammation, instrumentation, or operative history. Its histopathological diversity can create diagnostic dilemmas and pathologists utilize morphological evaluation along with available immunohistochemical markers to navigate these challenges. Immunohistochemical assays currently do not designate or specify nephrogenic adenoma's potential putative cell of origin. Leveraging single-cell RNA sequencing technology, we nominated a principal cell collecting duct marker, L1 cell adhesion molecule (L1CAM), as a potential biomarker for nephrogenic adenoma. Immunohistochemical characterization revealed L1CAM to be positive in all 35 (100%) patient samples of nephrogenic adenoma; negative expression was seen in the benign urothelium, benign prostatic glands, urothelial carcinoma in situ, prostatic adenocarcinoma, majority of high-grade urothelial carcinoma, and metastatic urothelial carcinoma. In the study, we also utilized single-cell RNA sequencing to nominate a novel compendium of biomarkers specific for proximal tubule, loop of Henle, and distal tubule (including principal and intercalated cells) which can be used to perform nephronal mapping utilizing RNA in situ hybridization and immunohistochemistry technology. Employing this technique on nephrogenic adenoma we found enrichment of both principal cell marker L1CAM and, the proximal tubule types-A and -B cells markers, PDZKI1P1 and PIGR respectively. The cell type markers for the intercalated cell of distal tubules (LINC01187 and FOXI1), and the loop of Henle (UMOD and IRX5), were found to be uniformly absent in nephrogenic adenoma. Overall, our findings show that based on cell type-specific implications of L1CAM expression, the shared expression pattern of L1CAM between distal tubule principal cell (P) cells and nephrogenic adenoma. L1CAM expression will be of potential value in assisting surgical pathologists towards a diagnosis of nephrogenic adenoma in challenging patient samples.

Single-cell analyses of renal cell cancers reveal insights into tumor microenvironment, cell of origin, and therapy response.

Diverse subtypes of renal cell carcinomas (RCCs) display a wide spectrum of histomorphologies, proteogenomic alterations, immune cell infiltration patterns, and clinical behavior. Delineating the cells of origin for different RCC subtypes will provide mechanistic insights into their diverse pathobiology. Here, we employed single-cell RNA sequencing (scRNA-seq) to develop benign and malignant renal cell atlases. Using a random forest model trained on this cell atlas, we predicted the putative cell of origin for more than 10 RCC subtypes. scRNA-seq also revealed several attributes of the tumor microenvironment in the most common subtype of kidney cancer, clear cell RCC (ccRCC). We elucidated an active role for tumor epithelia in promoting immune cell infiltration, potentially explaining why ccRCC responds to immune checkpoint inhibitors, despite having a low neoantigen burden. In addition, we characterized an association between high endothelial cell types and lack of response to immunotherapy in ccRCC. Taken together, these single-cell analyses of benign kidney and RCC provide insight into the putative cell of origin for RCC subtypes and highlight the important role of the tumor microenvironment in influencing ccRCC biology and response to therapy.

Leveraging artificial intelligence to predict ERG gene fusion status in prostate cancer.

BACKGROUND: TMPRSS2-ERG gene rearrangement, the most common E26 transformation specific (ETS) gene fusion within prostate cancer, is known to contribute to the pathogenesis of this disease and carries diagnostic annotations for prostate cancer patients clinically. The ERG rearrangement status in prostatic adenocarcinoma currently cannot be reliably identified from histologic features on H&E-stained slides alone and hence requires ancillary studies such as immunohistochemistry (IHC), fluorescent in situ hybridization (FISH) or next generation sequencing (NGS) for identification. METHODS: OBJECTIVE: We accordingly sought to develop a deep learning-based algorithm to identify ERG rearrangement status in prostatic adenocarcinoma based on digitized slides of H&E morphology alone. DESIGN: Setting, and Participants: Whole slide images from 392 in-house and TCGA cases were employed and annotated using QuPath. Image patches of 224 × 224 pixel were exported at 10 ×, 20 ×, and 40 × for input into a deep learning model based on MobileNetV2 convolutional neural network architecture pre-trained on ImageNet. A separate model was trained for each magnification. Training and test datasets consisted of 261 cases and 131 cases, respectively. The output of the model included a prediction of ERG-positive (ERG rearranged) or ERG-negative (ERG not rearranged) status for each input patch. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Various accuracy measurements including area under the curve (AUC) of the receiver operating characteristic (ROC) curves were used to evaluate the deep learning model. RESULTS AND LIMITATIONS: All models showed similar ROC curves with AUC results ranging between 0.82 and 0.85. The sensitivity and specificity of these models were 75.0% and 83.1% (20 × model), respectively. CONCLUSIONS: A deep learning-based model can successfully predict ERG rearrangement status in the majority of prostatic adenocarcinomas utilizing only H&E-stained digital slides. Such an artificial intelligence-based model can eliminate the need for using extra tumor tissue to perform ancillary studies in order to assess for ERG gene rearrangement in prostatic adenocarcinoma.

TRIM63 is a sensitive and specific biomarker for MiT family aberration-associated renal cell carcinoma.

Microphthalmia-associated transcription factor (MiT) family aberration-associated renal cell carcinoma (MiTF-RCC) is a subtype of renal cell carcinoma harboring recurrent chromosomal rearrangements involving TFE3 or TFEB genes. MiTF-RCC is morphologically diverse, can histologically resemble common RCC subtypes like clear cell RCC and papillary RCC, and often poses a diagnostic challenge in genitourinary clinical and pathology practice. To characterize the MiTF-RCC at the molecular level and identify biomarker signatures associated with MiTF-RCC, we analyzed RNAseq data from MiTF-RCC, other RCC subtypes and benign kidney. Upon identifying TRIM63 as a cancer-specific biomarker in MiTF-RCC, we evaluated its expression independently by RNA in situ hybridization (RNA-ISH) in whole tissue sections from 177 RCC cases. We specifically included 31 cytogenetically confirmed MiTF-RCC cases and 70 RCC cases suspicious for MiTF-RCC in terms of clinical and morphological features, to evaluate and compare TRIM63 RNA-ISH results with the results from TFE3/TFEB fluorescence in situ hybridization (FISH), which is the current clinical standard. We confirmed that TRIM63 mRNA was highly expressed in all classes of MiTF-RCC compared to other renal tumor categories, where it was mostly absent to low. While the TRIM63 RNA-ISH and TFE3/TFEB FISH results were largely concordant, importantly, TRIM63 RNA-ISH was strongly positive in TFE3 FISH false-negative cases with RBM10-TFE3 inversion. In conclusion, TRIM63 can serve as a diagnostic marker to distinguish MiTF-RCC from other renal tumor subtypes with overlapping morphology. We suggest a combination of TFE3/TFEB FISH and TRIM63 RNA-ISH assays to improve the accuracy and efficiency of MiTF-RCC diagnosis. Accurate diagnosis of MiTF-RCC and other RCC subtypes would enable effective targeted therapy and avoid poor therapeutic response due to tumor misclassification.

Clinicopathological characterisation of renal cell carcinoma in young adults: a contemporary update and review of literature.

AIMS: Renal cell carcinomas are relatively rare in children and young adults. While well characterised in adults, the morphological and molecular characterisation of these tumours in young patients is relatively lacking. The objective of this study was to explore the spectrum of renal cell carcinoma (RCC) subtypes in children and young adults and to determine their clinico-pathological, immunohistochemical and molecular characteristics by evaluating a large retrospective cohort of renal cell carcinoma patients age 30 years or younger. METHODS AND RESULTS: Sixty-eight cases with confirmed diagnosis of renal cell carcinoma at age 30 years or younger were identified at our institution. Clear cell carcinoma accounted for the most common subtype seen in this age group. Translocation renal cell carcinoma and rare familial syndrome subtypes such as succinate dehydrogenase deficient renal cell carcinoma and tuberous sclerosis complex-associated renal cell carcinoma were found relatively more frequently in this cohort. Despite applying the 2016 WHO classification criteria, a high proportion of the tumours in our series remained unclassified. CONCLUSIONS: Our results suggest that renal cell carcinoma in children and young adults is a relatively rare disease that shares many histological similarities to renal cell carcinoma occurring in adults and yet demonstrate some unique clinical-pathological differences. Microphthalmia-associated transcription (MiT) family translocation RCC and rare familial syndrome subtypes are relatively more frequent in the paediatric and adolescent age groups than in adults. Clear cell RCC still accounted for the most common subtype seen in this age group. MiT family translocation RCC patients presented with advanced stage disease and had poor clinical outcomes. The large and heterogeneous subgroup of unclassified renal cell carcinoma contains phenotypically distinct tumours with further potential for future subcategories in the renal cell carcinoma classification.

Immune associated LncRNAs identify novel prognostic subtypes of renal clear cell carcinoma.

Kidney Renal Clear Cell Carcinoma (KIRC) is a significant cause of cancer-related deaths. Here, we aim to identify the LncRNAs associated with the immune system and characterise their clinical utility in KIRC. A total of 504 patients' data was used from TCGA-GDC. In silico correlation analysis identified 143 LncRNAs associated with immune-related genes (r > 0.7, P < 0.05). K-means consensus method clustered KIRC samples in three immune clusters, namely cluster C1, C2, and C3 based on the expression of 143 immune-related LncRNAs. Kaplan-Meier analysis showed that C3 patients survived significantly worse than the other two clusters (P < 0.0001). A comparison of TCGA miRNA, mRNA cluster with immune cluster showed the independence and robustness of immune clusters (HR = 2.02 and P = 2.12 × 10-8 ). The GSEA and CIBERSORT analysis showed high enrichment of poorly activated T-cells in C3 patients. To define LncRNA immune prognostic signature, we randomly divided the TCGA sample into discovery and validation sets. By utilising multivariate Cox regression analysis, we identified and validated a seven LncRNA immune prognostic signature score (LIPS score) (HR = 1.43 and P = 2.73 × 10-6 ) in KIRC. Comparison of LIPS score with all the clinical factors validated its independence and superiority in KIRC prognosis. In summary, we identified LncRNAs associated with the immune system and showed the presence of prognostic subtypes of KIRC patients based on immune-related LncRNA expression. We also identified a novel immune LncRNA based gene-signature for KIRC patients' prognostication.

The landscape of antisense gene expression in human cancers.

High-throughput RNA sequencing has revealed more pervasive transcription of the human genome than previously anticipated. However, the extent of natural antisense transcripts' (NATs) expression, their regulation of cognate sense genes, and the role of NATs in cancer remain poorly understood. Here, we use strand-specific paired-end RNA sequencing (ssRNA-seq) data from 376 cancer samples covering nine tissue types to comprehensively characterize the landscape of antisense expression. We found consistent antisense expression in at least 38% of annotated transcripts, which in general is positively correlated with sense gene expression. Investigation of sense/antisense pair expressions across tissue types revealed lineage-specific, ubiquitous and cancer-specific antisense loci transcription. Comparisons between tumor and normal samples identified both concordant (same direction) and discordant (opposite direction) sense/antisense expression patterns. Finally, we provide OncoNAT, a catalog of cancer-related genes with significant antisense transcription, which will enable future investigations of sense/antisense regulation in cancer. Using OncoNAT we identified several functional NATs, including NKX2-1-AS1 that regulates the NKX2-1 oncogene and cell proliferation in lung cancer cells. Overall, this study provides a comprehensive account of NATs and supports a role for NATs' regulation of tumor suppressors and oncogenes in cancer biology.

Detection of 6 TFEB-amplified renal cell carcinomas and 25 renal cell carcinomas with MITF translocations: systematic morphologic analysis of 85 cases evaluated by clinical TFE3 and TFEB FISH assays.

Renal cell carcinomas with MITF aberrations demonstrate a wide morphologic spectrum, highlighting the need to consider these entities within the differential diagnosis of renal tumors encountered in clinical practice. Herein, we describe our experience with application of clinical fluorescence in situ hybridization (FISH) assays for detection of TFE3 and TFEB gene aberrations from 85 consecutive renal cell carcinoma cases submitted to our genitourinary FISH service. Results from 170 FISH assays performed on these tumors were correlated with available clinicopathologic findings. Ninety-eight percent of renal tumors submitted for FISH evaluation were from adult patients. Thirty-one (37%) tumors were confirmed to demonstrate MITF aberrations (21 TFE3 translocation, 4 TFEB translocation, and 6 TFEB amplification cases). Overall, renal cell carcinomas with MITF aberrations demonstrated morphologic features overlapping with clear cell, papillary, or clear cell papillary renal cell carcinomas. Renal cell carcinomas with MITF aberrations were significantly more likely to demonstrate dual (eosinophilic and clear) cytoplasmic tones (P=0.030), biphasic TFEB translocation renal cell carcinoma-like morphology (P=0.002), psammomatous calcifications (P=0.002), and nuclear pseudoinclusions (P=0.001) than renal cell carcinomas without MITF aberrations. Notably, 7/9 (78%) renal cell carcinomas exhibiting subnuclear clearing and linear nuclear array (6 of which showed high World Health Organization/International Society of Urological Pathology nucleolar grade) demonstrated TFE3 translocation, an association that was statistically significant when compared with renal cell carcinomas without MITF aberrations (P=0.009). In this cohort comprising consecutive cases, TFEB-amplified renal cell carcinomas were more commonly identified than renal cell carcinomas with TFEB translocations, and four (67%) of these previously unreported TFEB-amplified renal cell carcinomas demonstrated oncocytic and papillary features with a high World Health Organization/International Society of Urological Pathology nucleolar grade. In summary, TFE3 and TFEB FISH evaluation aids in identification and accurate classification of renal cell carcinomas with MITF aberrations, including TFEB-amplified renal cell carcinoma, which may demonstrate aggressive behavior.

The mutational landscape of lethal castration-resistant prostate cancer.

Characterization of the prostate cancer transcriptome and genome has identified chromosomal rearrangements and copy number gains and losses, including ETS gene family fusions, PTEN loss and androgen receptor (AR) amplification, which drive prostate cancer development and progression to lethal, metastatic castration-resistant prostate cancer (CRPC). However, less is known about the role of mutations. Here we sequenced the exomes of 50 lethal, heavily pre-treated metastatic CRPCs obtained at rapid autopsy (including three different foci from the same patient) and 11 treatment-naive, high-grade localized prostate cancers. We identified low overall mutation rates even in heavily treated CRPCs (2.00 per megabase) and confirmed the monoclonal origin of lethal CRPC. Integrating exome copy number analysis identified disruptions of CHD1 that define a subtype of ETS gene family fusion-negative prostate cancer. Similarly, we demonstrate that ETS2, which is deleted in approximately one-third of CRPCs (commonly through TMPRSS2:ERG fusions), is also deregulated through mutation. Furthermore, we identified recurrent mutations in multiple chromatin- and histone-modifying genes, including MLL2 (mutated in 8.6% of prostate cancers), and demonstrate interaction of the MLL complex with the AR, which is required for AR-mediated signalling. We also identified novel recurrent mutations in the AR collaborating factor FOXA1, which is mutated in 5 of 147 (3.4%) prostate cancers (both untreated localized prostate cancer and CRPC), and showed that mutated FOXA1 represses androgen signalling and increases tumour growth. Proteins that physically interact with the AR, such as the ERG gene fusion product, FOXA1, MLL2, UTX (also known as KDM6A) and ASXL1 were found to be mutated in CRPC. In summary, we describe the mutational landscape of a heavily treated metastatic cancer, identify novel mechanisms of AR signalling deregulated in prostate cancer, and prioritize candidates for future study.

Two-pass alignment improves novel splice junction quantification.

MOTIVATION: Discovery of novel splicing from RNA sequence data remains a critical and exciting focus of transcriptomics, but reduced alignment power impedes expression quantification of novel splice junctions. RESULTS: Here, we profile performance characteristics of two-pass alignment, which separates splice junction discovery from quantification. Per sample, across a variety of transcriptome sequencing datasets, two-pass alignment improved quantification of at least 94% of simulated novel splice junctions, and provided as much as 1.7-fold deeper median read depth over those splice junctions. We further demonstrate that two-pass alignment works by increasing alignment of reads to splice junctions by short lengths, and that potential alignment errors are readily identifiable by simple classification. Taken together, two-pass alignment promises to advance quantification and discovery of novel splicing events. CONTACT: arul@med.umich.edu, nesvi@med.umich.edu AVAILABILITY AND IMPLEMENTATION: Two-pass alignment was implemented here as sequential alignment, genome indexing, and re-alignment steps with STAR. Full parameters are provided in Supplementary Table 2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrative molecular concept modeling of prostate cancer progression.

Despite efforts to profile prostate cancer, the genetic alterations and biological processes that correlate with the observed histological progression are unclear. Using laser-capture microdissection to isolate 101 cell populations, we have profiled prostate cancer progression from benign epithelium to metastatic disease. By analyzing expression signatures in the context of over 14,000 'molecular concepts', or sets of biologically connected genes, we generated an integrative model of progression. Molecular concepts that demarcate critical transitions in progression include protein biosynthesis, E26 transformation-specific (ETS) family transcriptional targets, androgen signaling and cell proliferation. Of note, relative to low-grade prostate cancer (Gleason pattern 3), high-grade cancer (Gleason pattern 4) shows an attenuated androgen signaling signature, similar to metastatic prostate cancer, which may reflect dedifferentiation and explain the clinical association of grade with prognosis. Taken together, these data show that analyzing gene expression signatures in the context of a compendium of molecular concepts is useful in understanding cancer biology.