Proteomic insights into paediatric cancer: Unravelling molecular signatures and therapeutic opportunities.

Survival rates in some paediatric cancers have improved greatly over recent decades, in part due to the identification of diagnostic, prognostic and predictive molecular signatures, and the development of risk-directed therapies. However, other paediatric cancers have proved difficult to treat, and there is an urgent need to identify novel biomarkers that reveal therapeutic opportunities. The proteome is the total set of expressed proteins present in a cell or tissue at a point in time, and is vastly more dynamic than the genome. Proteomics holds significant promise for cancer research, as proteins are ultimately responsible for cellular phenotype and are the target of most anticancer drugs. Here, we review the discoveries, opportunities and challenges of proteomic analyses in paediatric cancer, with a focus on mass spectrometry (MS)-based approaches. Accelerating incorporation of proteomics into paediatric precision medicine has the potential to improve survival and quality of life for children with cancer.

Retrospective analysis of clinical characteristics and outcomes of patients with carcinoma of unknown primary from three tertiary centers in Australia.

BACKGROUND: Carcinoma of unknown primary (CUP) remains an important tumor entity and a disproportionate cause of cancer mortality. Little is known about the contemporary clinical characteristics, treatment patterns, and outcomes of CUP patients based on updated international classification guidelines. We evaluated a contemporary CUP cohort to provide insight into current clinical practice and the impact of tissue of origin assignment, site-specific and empirical therapy in a real-world setting. METHODS: We conducted a retrospective cohort study of CUP patients, as defined by the updated European Society of Medical Oncology (ESMO) 2023 guidelines, across three tertiary referral centers in Australia between 2015 and 2022. We analyzed clinical characteristics, treatment patterns, and survival outcomes using the Kaplan-Meier method and Cox regression proportional hazard model between favorable and unfavorable risk groups. RESULTS: We identified a total of 123 CUP patients (n = 86 unfavorable, n = 37 favorable risk as per the 2023 ESMO guidelines). Sixty-four patients (52%) were assigned a tissue of origin by the treating clinician. Median progression free survival (PFS) was 6.8 (95% confidence interval (CI) 5.1-12.1) months and overall survival (OS) 10.2 (95% CI 6.0-18.5) months. Unfavorable risk (hazard ratio [HR] 2.9, p = 0.006), poor performance status (HR 2.8, p < 0.001), and non-squamous histology (HR 2.5, p < 0.05) were associated with poor survival outcome. A total of 70 patients (57%) proceeded to systemic therapy. In patients with non-squamous histology and unfavorable risk, site-specific therapy compared to empirical chemotherapy did not improve outcome (median OS 8.2 vs. 11.8 months, p = 0.7). CONCLUSIONS: In this real-world cohort, CUP presentations were heterogenous. Overall survival and rates of systemic treatment were poor. Poor performance status and unfavorable risk were associated with worse survival. For most patients, site-specific therapy did not improve survival outcome. Improved and timely access to diagnostic tests and therapeutics for this group of patients is urgently required.

Proteomic-based stratification of intermediate-risk prostate cancer patients.

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

Quantitative proteomic studies addressing unmet clinical needs in sarcoma.

Sarcoma is a rare and complex disease comprising over 80 malignant subtypes that is frequently characterized by poor prognosis. Challenges in clinical management include uncertainties in diagnosis and disease classification, limited prognostic and predictive biomarkers, incompletely understood disease heterogeneity among and within subtypes, lack of effective treatment options, and limited progress in identifying new drug targets and novel therapeutics. Proteomics refers to the study of the entire complement of proteins expressed in specific cells or tissues. Advances in proteomics have included the development of quantitative mass spectrometry (MS)-based technologies which enable analysis of large numbers of proteins with relatively high throughput, enabling proteomics to be studied on a scale that has not previously been possible. Cellular function is determined by the levels of various proteins and their interactions, so proteomics offers the possibility of new insights into cancer biology. Sarcoma proteomics therefore has the potential to address some of the key current challenges described above, but it is still in its infancy. This review covers key quantitative proteomic sarcoma studies with findings that pertain to clinical utility. Proteomic methodologies that have been applied to human sarcoma research are briefly described, including recent advances in MS-based proteomic technology. We highlight studies that illustrate how proteomics may aid diagnosis and improve disease classification by distinguishing sarcoma histologies and identify distinct profiles within histological subtypes which may aid understanding of disease heterogeneity. We also review studies where proteomics has been applied to identify prognostic, predictive and therapeutic biomarkers. These studies traverse a range of histological subtypes including chordoma, Ewing sarcoma, gastrointestinal stromal tumors, leiomyosarcoma, liposarcoma, malignant peripheral nerve sheath tumors, myxofibrosarcoma, rhabdomyosarcoma, synovial sarcoma, osteosarcoma, and undifferentiated pleomorphic sarcoma. Critical questions and unmet needs in sarcoma which can potentially be addressed with proteomics are outlined.

CRISPR screens identify gene targets at breast cancer risk loci.

BACKGROUND: Genome-wide association studies (GWAS) have identified > 200 loci associated with breast cancer risk. The majority of candidate causal variants are in non-coding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association, and identifying the phenotype it mediates, is a major challenge in the interpretation and translation of GWAS. RESULTS: Here, we show that pooled CRISPR screens are highly effective at identifying GWAS target genes and defining the cancer phenotypes they mediate. Following CRISPR mediated gene activation or suppression, we measure proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on DNA repair. We perform 60 CRISPR screens and identify 20 genes predicted with high confidence to be GWAS targets that promote cancer by driving proliferation or modulating the DNA damage response in breast cells. We validate the regulation of a subset of these genes by breast cancer risk variants. CONCLUSIONS: We demonstrate that phenotypic CRISPR screens can accurately pinpoint the gene target of a risk locus. In addition to defining gene targets of risk loci associated with increased breast cancer risk, we provide a platform for identifying gene targets and phenotypes mediated by risk variants.

Opportunities for pharmacoproteomics in biomarker discovery.

Proteomic data are a uniquely valuable resource for drug response prediction and biomarker discovery because most drugs interact directly with proteins in target cells rather than with DNA or RNA. Recent advances in mass spectrometry and associated processing methods have enabled the generation of large-scale proteomic datasets. Here we review the significant opportunities that currently exist to combine large-scale proteomic data with drug-related research, a field termed pharmacoproteomics. We describe successful applications of drug response prediction using molecular data, with an emphasis on oncology. We focus on technical advances in data-independent acquisition mass spectrometry (DIA-MS) that can facilitate the discovery of protein biomarkers for drug responses, alongside the increased availability of big biomedical data. We spotlight new opportunities for machine learning in pharmacoproteomics, driven by the combination of these large datasets and improved high-performance computing. Finally, we explore the value of pre-clinical models for pharmacoproteomic studies and the accompanying challenges of clinical validation. We propose that pharmacoproteomics offers the potential for novel discovery and innovation within the cancer landscape.

Clinical applications of mass spectrometry-based proteomics in cancer: Where are we?

Tumor tissue processing methodologies in combination with data-independent acquisition mass spectrometry (DIA-MS) have emerged that can comprehensively analyze the proteome of multiple tumor samples accurately and reproducibly. Increasing recognition and adoption of these technologies has resulted in a tranche of studies providing novel insights into cancer classification systems, functional tumor biology, cancer biomarkers, treatment response and drug targets. Despite this, with some limited exceptions, MS-based proteomics has not yet been implemented in routine cancer clinical practice. Here, we summarize the use of DIA-MS in studies that may pave the way for future clinical cancer applications, and highlight the role of alternative MS technologies and multi-omic strategies. We discuss limitations and challenges of studies in this field to date and propose steps for integrating proteomic data into the cancer clinic.

TOP3A amplification and ATRX inactivation are mutually exclusive events in pediatric osteosarcomas using ALT.

In some types of cancer, telomere length is maintained by the alternative lengthening of telomeres (ALT) mechanism. In many ALT cancers, the α-thalassemia/mental retardation syndrome X-linked (ATRX) gene is mutated leading to the conclusion that the ATRX complex represses ALT. Here, we report that most high-grade pediatric osteosarcomas maintain their telomeres by ALT, and that the majority of these ALT tumors are ATRX wild-type (wt) and instead carry an amplified 17p11.2 chromosomal region containing TOP3A. We found that TOP3A was overexpressed in the ALT-positive ATRX-wt tumors consistent with its amplification. We demonstrated the functional significance of these results by showing that TOP3A overexpression in ALT cancer cells countered ATRX-mediated ALT inhibition and that TOP3A knockdown disrupted the ALT phenotype in ATRX-wt cells. Moreover, we report that TOP3A is required for proper BLM localization and promotes ALT DNA synthesis in ALT cell lines. Collectively, our results identify TOP3A as a major ALT player and potential therapeutic target.

Stanniocalcin2, but Not Stanniocalcin1, Responds to Hypoxia in a HIF1-Dependent Manner in the Retina.

The quest for neuroprotective factors that can prevent or slow down the progression of retinal degeneration is still ongoing. Acute hypoxic stress has been shown to provide transient protection against subsequent damage in the retina. Stanniocalcins - STC1 and STC2 - are secreted glycoproteins that are hypoxia-regulated and were shown to be cytoprotective in various in vitro studies. Hence, we investigated the expression of stanniocalcins in the normal, degenerating and hypoxic retina. We show that the expression of Stc1 and Stc2 in the retina was detectable as early as postnatal day 10 and persisted during aging. Retinal expression of Stc2, but not Stc1, was induced in mice in an in vivo model of acute hypoxia and a genetic model of chronic hypoxia. Furthermore, we show that HIF1, not HIF2, is responsible for regulating Stc2 in cells with the molecular response to hypoxia activated due to the absence of von Hippel Lindau protein. Surprisingly, Stc2 was not normally expressed in photoreceptors but in the inner retina, as shown by laser capture microdissection and immunofluorescence data. The expression of both Stc1 and Stc2 remained unchanged in the degenerative retina with an almost complete loss of photoreceptors, confirming their expression in the inner retina. However, the absence of either Stc1 or Stc2 had no effect on retinal architecture, as was evident from retinal morphology of the respective knockout mice. Taken together our data provides evidence for the differential regulation of STC1 and STC2 in the retina and the prospect of investigating STC2 as a retinal neuroprotective factor.

Pan-cancer proteomic map of 949 human cell lines.

The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk.

qmotif: determination of telomere content from whole-genome sequence data.

Motivation: Changes in telomere length have been observed in cancer and can be indicative of mechanisms involved in carcinogenesis. Most methods used to estimate telomere length require laboratory analysis of DNA samples. Here, we present qmotif, a fast and easy tool that determines telomeric repeat sequences content as an estimate of telomere length directly from whole-genome sequencing. Results: qmotif shows similar results to quantitative PCR, the standard method for high-throughput clinical telomere length quantification. qmotif output correlates strongly with the output of other tools for determining telomere sequence content, TelSeq and TelomereHunter, but can run in a fraction of the time-usually under a minute. Availability and implementation: qmotif is implemented in Java and source code is available at https://github.com/AdamaJava/adamajava, with instructions on how to build and use the application available from https://adamajava.readthedocs.io/en/latest/. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

The C-Circle Biomarker Is Secreted by Alternative-Lengthening-of-Telomeres Positive Cancer Cells inside Exosomes and Provides a Blood-Based Diagnostic for ALT Activity.

C-Circles, self-primed telomeric C-strand templates for rolling circle amplification, are the only known alternative-lengthening-of-telomeres (ALT)-specific molecule. However, little is known about the biology of C-Circles and if they may be clinically useful. Here we show that C-Circles are secreted by ALT+ cancer cells inside exosomes, and that a blood-based C-Circle Assay (CCA) can provide an accurate diagnostic for ALT activity. Extracellular vesicles were isolated by differential centrifugation from the growth media of lung adenocarcinoma, glioblastoma, neuroblastoma, osteosarcoma, and soft tissue sarcoma cell lines, and C-Circles were detected in the exosome fraction from all eleven ALT+ cancer cell lines and not in any extracellular fraction from the eight matching telomerase positive cancer cell lines or the normal fibroblast strain. The existence of C-Circles in ALT+ exosomes was confirmed with exosomes isolated by iodixanol gradient separation and CD81-immunoprecipitation, and C-Circles in the exosomes were protected from nucleases. On average, 0.4% of the total ALT+ intracellular C-Circles were secreted in the exosomes every 24 h. Comparing the serum-based and tumor-based CCAs in 35 high risk neuroblastoma patients divided randomly into ALT+ threshold derivation and validation groups, we found the serum-based CCA to have 100% sensitivity (6/6), 70% specificity (7/10), and 81% concordance (13/16). We conclude that the secretion of C-Circles by ALT+ cancer cells in the exosomes provides a stable blood-based biomarker and a potential clinical diagnostic for ALT activity.

Functional characterization of miR-708 microRNA in telomerase positive and negative human cancer cells.

Activation of a telomere length maintenance mechanism (TMM), including telomerase and alternative lengthening of telomeres (ALT), is essential for replicative immortality of tumor cells, although its regulatory mechanisms are incompletely understood. We conducted a microRNA (miRNA) microarray analysis on isogenic telomerase positive (TEP) and ALT cancer cell lines. Amongst nine miRNAs that showed difference in their expression in TEP and ALT cancer cells in array analysis, miR-708 was selected for further analysis since it was consistently highly expressed in a large panel of ALT cells. miR-708 in TEP and ALT cancer cells was not correlated with C-circle levels, an established feature of ALT cells. Its overexpression induced suppression of cell migration, invasion, and angiogenesis in both TEP and ALT cells, although cell proliferation was inhibited only in TEP cells suggesting that ALT cells may have acquired the ability to escape inhibition of cell proliferation by sustained miR-708 overexpression. Further, cell proliferation regulation in TEP cells by miR708 appears to be through the CARF-p53 pathway. We demonstrate here that miR-708 (i) is the first miRNA shown to be differentially regulated in TEP and ALT cancer cells, (ii) possesses tumor suppressor function, and (iii) deregulates CARF and p21WAF1-mediated signaling to limit proliferation in TEP cells.

A novel cause of DKC1-related bone marrow failure: Partial deletion of the 3' untranslated region.

Telomere biology disorders (TBDs), including dyskeratosis congenita (DC), are a group of rare inherited diseases characterized by very short telomeres. Mutations in the components of the enzyme telomerase can lead to insufficient telomere maintenance in hematopoietic stem cells, resulting in the bone marrow failure that is characteristic of these disorders. While an increasing number of genes are being linked to TBDs, the causative mutation remains unidentified in 30-40% of patients with DC. There is therefore a need for whole genome sequencing (WGS) in these families to identify novel genes, or mutations in regulatory regions of known disease-causing genes. Here we describe a family in which a partial deletion of the 3' untranslated region (3' UTR) of DKC1, encoding the protein dyskerin, was identified by WGS, despite being missed by whole exome sequencing. The deletion segregated with disease across the family and resulted in reduced levels of DKC1 mRNA in the proband. We demonstrate that the DKC1 3' UTR contains two polyadenylation signals, both of which were removed by this deletion, likely causing mRNA instability. Consistent with the major function of dyskerin in stabilization of the RNA subunit of telomerase, hTR, the level of hTR was also reduced in the proband, providing a molecular basis for his very short telomeres. This study demonstrates that the terminal region of the 3' UTR of the DKC1 gene is essential for gene function and illustrates the importance of analyzing regulatory regions of the genome for molecular diagnosis of inherited disease.

Targeted Therapy of TERT-Rearranged Neuroblastoma with BET Bromodomain Inhibitor and Proteasome Inhibitor Combination Therapy.

PURPOSE: TERT gene rearrangement with transcriptional superenhancers leads to TERT overexpression and neuroblastoma. No targeted therapy is available for clinical trials in patients with TERT-rearranged neuroblastoma. EXPERIMENTAL DESIGN: Anticancer agents exerting the best synergistic anticancer effects with BET bromodomain inhibitors were identified by screening an FDA-approved oncology drug library. The synergistic effects of the BET bromodomain inhibitor OTX015 and the proteasome inhibitor carfilzomib were examined by immunoblot and flow cytometry analysis. The anticancer efficacy of OTX015 and carfilzomib combination therapy was investigated in mice xenografted with TERT-rearranged neuroblastoma cell lines or patient-derived xenograft (PDX) tumor cells, and the role of TERT reduction in the anticancer efficacy was examined through rescue experiments in mice. RESULTS: The BET bromodomain protein BRD4 promoted TERT-rearranged neuroblastoma cell proliferation through upregulating TERT expression. Screening of an approved oncology drug library identified the proteasome inhibitor carfilzomib as the agent exerting the best synergistic anticancer effects with BET bromodomain inhibitors including OTX015. OTX015 and carfilzomib synergistically reduced TERT protein expression, induced endoplasmic reticulum stress, and induced TERT-rearranged neuroblastoma cell apoptosis which was blocked by TERT overexpression and endoplasmic reticulum stress antagonists. In mice xenografted with TERT-rearranged neuroblastoma cell lines or PDX tumor cells, OTX015 and carfilzomib synergistically blocked TERT expression, induced tumor cell apoptosis, suppressed tumor progression, and improved mouse survival, which was largely reversed by forced TERT overexpression. CONCLUSIONS: OTX015 and carfilzomib combination therapy is likely to be translated into the first clinical trial of a targeted therapy in patients with TERT-rearranged neuroblastoma.

Role of POT1 in Human Cancer.

Telomere abnormalities facilitate cancer development by contributing to genomic instability and cellular immortalization. The Protection of Telomeres 1 (POT1) protein is an essential subunit of the shelterin telomere binding complex. It directly binds to single-stranded telomeric DNA, protecting chromosomal ends from an inappropriate DNA damage response, and plays a role in telomere length regulation. Alterations of POT1 have been detected in a range of cancers. Here, we review the biological functions of POT1, the prevalence of POT1 germline and somatic mutations across cancer predisposition syndromes and tumor types, and the dysregulation of POT1 expression in cancers. We propose a framework for understanding how POT1 abnormalities may contribute to oncogenesis in different cell types. Finally, we summarize the clinical implications of POT1 alterations in the germline and in cancer, and possible approaches for the development of targeted cancer therapies.

Strategies to enable large-scale proteomics for reproducible research.

Reproducible research is the bedrock of experimental science. To enable the deployment of large-scale proteomics, we assess the reproducibility of mass spectrometry (MS) over time and across instruments and develop computational methods for improving quantitative accuracy. We perform 1560 data independent acquisition (DIA)-MS runs of eight samples containing known proportions of ovarian and prostate cancer tissue and yeast, or control HEK293T cells. Replicates are run on six mass spectrometers operating continuously with varying maintenance schedules over four months, interspersed with ~5000 other runs. We utilise negative controls and replicates to remove unwanted variation and enhance biological signal, outperforming existing methods. We also design a method for reducing missing values. Integrating these computational modules into a pipeline (ProNorM), we mitigate variation among instruments over time and accurately predict tissue proportions. We demonstrate how to improve the quantitative analysis of large-scale DIA-MS data, providing a pathway toward clinical proteomics.

End Products of Telomere Research.

Most rare inherited telomere biology disorders and some common aging-related diseases are associated with shortened telomeres. In this issue of Cell Stem Cell, insights into one of the rarest genetic causes of these disorders led to the discovery (Nagpal et al., 2020) of small molecules that lengthen telomeres.

Author Correction: The FANCM-BLM-TOP3A-RMI complex suppresses alternative lengthening of telomeres (ALT).

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