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Diet is a robust entrainment cue that regulates diurnal rhythms of the gut microbiome. We and others have shown that disruption of the circadian clock drives the progression of colorectal cancer (CRC). While certain bacterial species have been suggested to play driver roles in CRC, it is unknown whether the intestinal clock impinges on the microbiome to accelerate CRC pathogenesis. To address this, genetic disruption of the circadian clock, in an Apc-driven mouse model of CRC, was used to define the impact on the gut microbiome. When clock disruption is combined with CRC, metagenomic sequencing identified dysregulation of many bacterial genera including Bacteroides, Helicobacter, and Megasphaera. We identify functional changes to microbial pathways including dysregulated nucleic acid, amino acid, and carbohydrate metabolism, as well as disruption of intestinal barrier function. Our findings suggest that clock disruption impinges on microbiota composition and intestinal permeability that may contribute to CRC pathogenesis.

Despite efforts to understand breast cancer biology, metastatic disease remains a clinical challenge. Identifying suppressors of breast cancer progression and mechanisms of transition to more invasive phenotypes could provide game changing therapeutic opportunities. Transcriptional deregulation is central to all malignancies, highlighted by the extensive reprogramming of regulatory elements that underlie oncogenic programs. Among these, super-enhancers (SEs) stand out due to their enrichment in genes controlling cancer hallmarks. To reveal novel breast cancer dependencies, we integrated the analysis of the SE landscape with master regulator activity inference for a series of breast cancer cell lines. As a result, we identified T - h elper-inducing Poxviruses and Zinc-finger ( PO Z)/ K rüppel-like factor (ThPOK, ZBTB7B ), a CD4 + cell lineage commitment factor, as a breast cancer master regulator that is recurrently associated with a SE. ThPOK expression is highest in luminal breast cancer but is significantly reduced in the basal subtype. Manipulation of ThPOK levels in cell lines shows that its repressive function restricts breast cancer cells to an epithelial phenotype by suppressing the expression of genes involved in the epithelial-mesenchymal transition (EMT), WNT/β-catenin target genes, and the pro-metastatic TGFβ pathway. Our study reveals ThPOK as a master transcription factor that restricts the acquisition of metastatic features in breast cancer cells.

Prostate cancer is frequently treated with radiotherapy. Unfortunately, aggressive radioresistant relapses can arise, and the molecular underpinnings of radioresistance are unknown. Modern clinical radiotherapy is evolving to deliver higher doses of radiation in fewer fractions (hypofractionation). We therefore analyzed genomic, transcriptomic, and proteomic data to characterize prostate cancer radioresistance in cells treated with both conventionally fractionated and hypofractionated radiotherapy. Independent of fractionation schedule, resistance to radiotherapy involved massive genomic instability and abrogation of DNA mismatch repair. Specific prostate cancer driver genes were modulated at the RNA and protein levels, with distinct protein subcellular responses to radiotherapy. Conventional fractionation led to a far more aggressive biomolecular response than hypofractionation. Testing preclinical candidates identified in cell lines, we revealed POLQ (DNA Polymerase Theta) as a radiosensitizer. POLQ-modulated radioresistance in model systems and was predictive of it in large patient cohorts. The molecular response to radiation is highly multimodal and sheds light on prostate cancer lethality.SignificanceRadiation is standard of care in prostate cancer. Yet, we have little understanding of its failure. We demonstrate a new paradigm that radioresistance is fractionation specific and identified POLQ as a radioresistance modulator.

The insights into interactions between host genetics and gut microbiome (GM) in colorectal tumor susceptibility (CTS) remains lacking. We used Collaborative Cross mouse population model to identify genetic and microbial determinants of Azoxymethane-induced CTS. We identified 4417 CTS-associated single nucleotide polymorphisms (SNPs) containing 334 genes that were transcriptionally altered in human colorectal cancers (CRCs) and consistently clustered independent human CRC cohorts into two subgroups with different prognosis. We discovered a set of genera in early-life associated with CTS and defined a 16-genus signature that accurately predicted CTS, the majority of which were correlated with human CRCs. We identified 547 SNPs associated with abundances of these genera. Mediation analysis revealed GM as mediators partially exerting the effect of SNP UNC3869242 within Duox2 on CTS. Intestine cell-specific depletion of Duox2 altered GM composition and contribution of Duox2 depletion to CTS was significantly influenced by GM. Our findings provide potential novel targets for personalized CRC prevention and treatment.

PurposeThe purpose of this study was to evaluate RB1 expression and survival across ovarian carcinoma histotypes and how co-occurrence of BRCA1 or BRCA2 (BRCA) alterations and RB1 loss influences survival in tubo-ovarian high-grade serous carcinoma (HGSC).Experimental designRB1 protein expression was classified by immunohistochemistry in ovarian carcinomas of 7,436 patients from the Ovarian Tumor Tissue Analysis consortium. We examined RB1 expression and germline BRCA status in a subset of 1,134 HGSC, and related genotype to overall survival (OS), tumor-infiltrating CD8+ lymphocytes, and transcriptomic subtypes. Using CRISPR-Cas9, we deleted RB1 in HGSC cells with and without BRCA1 alterations to model co-loss with treatment response. We performed whole-genome and transcriptome data analyses on 126 patients with primary HGSC to characterize tumors with concurrent BRCA deficiency and RB1 loss.ResultsRB1 loss was associated with longer OS in HGSC but with poorer prognosis in endometrioid ovarian carcinoma. Patients with HGSC harboring both RB1 loss and pathogenic germline BRCA variants had superior OS compared with patients with either alteration alone, and their median OS was three times longer than those without pathogenic BRCA variants and retained RB1 expression (9.3 vs. 3.1 years). Enhanced sensitivity to cisplatin and paclitaxel was seen in BRCA1-altered cells with RB1 knockout. Combined RB1 loss and BRCA deficiency correlated with transcriptional markers of enhanced IFN response, cell-cycle deregulation, and reduced epithelial-mesenchymal transition. CD8+ lymphocytes were most prevalent in BRCA-deficient HGSC with co-loss of RB1.ConclusionsCo-occurrence of RB1 loss and BRCA deficiency was associated with exceptionally long survival in patients with HGSC, potentially due to better treatment response and immune stimulation.

Precision medicine holds great promise for improving cancer outcomes. Yet, there are large inequities in the demographics of patients from whom genomic data and models, including patient-derived xenografts (PDX), are developed and for whom treatments are optimized. In this study, we developed a genetic ancestry pipeline for the Cancer Genomics Cloud, which we used to assess the diversity of models currently available in the National Cancer Institute-supported PDX Development and Trial Centers Research Network (PDXNet). We showed that there is an under-representation of models derived from patients of non-European ancestry, consistent with other cancer model resources. We discussed these findings in the context of disparities in cancer incidence and outcomes among demographic groups in the US, as well as power analyses for biomarker discovery, to highlight the immediate need for developing models from minority populations to address cancer health equity in precision medicine. Our analyses identified key priority disparity-associated cancer types for which new models should be developed.SignificanceUnderstanding whether and how tumor genetic factors drive differences in outcomes among U.S. minority groups is critical to addressing cancer health disparities. Our findings suggest that many additional models will be necessary to understand the genome-driven sources of these disparities.

Glioblastoma (GBM) is the deadliest form of primary brain tumor with limited treatment options. Recent studies have profiled GBM tumor heterogeneity, revealing numerous axes of variation that explain the molecular and spatial features of the tumor. Here, we seek to bridge descriptive characterization of GBM cell type heterogeneity with the functional role of individual populations within the tumor. Our lens leverages a gene program-centric meta-atlas of published transcriptomic studies to identify commonalities between diverse tumors and cell types in order to decipher the mechanisms that drive them. This approach led to the discovery of a tumor-derived stem cell population with mixed vascular and neural stem cell features, termed a neurovascular progenitor (NVP). Following in situ validation and molecular characterization of NVP cells in GBM patient samples, we characterized their function in vivo. Genetic depletion of NVP cells resulted in altered tumor cell composition, fewer cycling cells, and extended survival, underscoring their critical functional role. Clonal analysis of primary patient tumors in a human organoid tumor transplantation system demonstrated that the NVP has dual potency, generating both neuronal and vascular tumor cells. Although NVP cells comprise a small fraction of the tumor, these clonal analyses demonstrated that they strongly contribute to the total number of cycling cells in the tumor and generate a defined subset of the whole tumor. This study represents a paradigm by which cell type-specific interrogation of tumor populations can be used to study functional heterogeneity and therapeutically targetable vulnerabilities of GBM.

The early 2-factor (E2F) family of transcription factors, including E2F1 through 8, plays a critical role in apoptosis, metabolism, proliferation, and angiogenesis within glioblastoma (GBM). However, the specific functions of E2F transcription factors (E2Fs) and their impact on the malignancy of Bevacizumab (BVZ)-responsive GBM subtypes remain unclear. This study used data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI), and Gene Expression Omnibus (GEO) to explore the impact of eight E2F family members on the clinical characteristics of BVZ-responsive GBM subtypes and possible mechanisms of recurrence after BVZ treatment. Using machine learning algorithms, including TreeBagger and deep neural networks, we systematically predicted and validated GBM patient survival terms based on the expression profiles of E2Fs across BVZ-responsive GBM subtypes. Our bioinformatics analyses suggested that a significant increase in E2F8 post-BVZ treatment may enhance the function of angiogenesis and stem cell proliferation, implicating this factor as a candidate mechanism of GBM recurrence after treatment. In addition, BVZ treatment in unresponsive GBM patients may potentially worsen disease progression. These insights underscore that E2F family members play important roles in GBM malignancy and BVZ treatment response, highlighting their potential as prognostic biomarkers, therapeutic targets, and recommending precision BVZ treatment to individual GBM patients.

Glioblastoma (GBM) is the most common malignant primary brain tumor and remains incurable. Previous work has shown that systemic administration of Decitabine (DAC) induces sufficient expression of cancer-testis antigens (CTA) in GBM for targeting by adoptive T-cell therapy in vivo. However, the mechanisms by which DAC enhances immunogenicity in GBM remain to be elucidated. Using New York esophageal squamous cell carcinoma 1 (NY-ESO-1) as a representative inducible CTA, we demonstrate in patient tissue, immortalized glioma cells, and primary patient-derived gliomaspheres that basal CTA expression is restricted by promoter hypermethylation in gliomas. DAC treatment of glioma cells specifically inhibits DNA methylation silencing to render NY-ESO-1 and other CTA into inducible tumor antigens at single-cell resolution. Functionally, NY-ESO-1 T-cell receptor-engineered effector cell targeting of DAC-induced antigen in primary glioma cells promotes specific and polyfunctional T-cell cytokine profiles. In addition to induction of CTA, DAC concomitantly reactivates tumor-intrinsic human endogenous retroviruses, interferon response signatures, and MHC-I. Overall, we demonstrate that DAC induces targetable tumor antigen and enhances T-cell functionality against GBM, ultimately contributing to the improvement of targeted immune therapies in glioma.SignificanceThis study dissects the tumor-intrinsic epigenetic and transcriptional mechanisms underlying enhanced T-cell functionality targeting decitabine-induced cancer-testis antigens in glioma. Our findings demonstrate concomitant induction of tumor antigens, reactivation of human endogenous retroviruses, and stimulation of interferon signaling as a mechanistic rationale to epigenetically prime human gliomas to immunotherapeutic targeting.

Accurate diagnosis of lung cancer is important for treatment decision-making. Tumor biopsy and histologic examination are the standard for determining histologic lung cancer subtypes. Liquid biopsy, particularly cell-free DNA (cfDNA), has recently shown promising results in cancer detection and classification. In this study, we investigate the potential of cfDNA methylome for the noninvasive classification of lung cancer histologic subtypes. We focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcriptional activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in cross-validation and an AUC of 0.747 in the independent validation. Tumor copy-number alterations inferred from cfDNA methylome analysis revealed potential for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasive lung cancer subtyping, offering insights for cancer monitoring and early detection.SignificanceThis study explores the use of cfDNA methylomes for the classification of lung cancer subtypes, vital for effective treatment. By identifying specific methylation markers in tumor tissues, we developed a robust classification model achieving high accuracy for noninvasive subtype detection. This cfDNA methylome approach offers promising avenues for early detection and monitoring.

Whole-genome bisulfite sequencing (BS-Seq) measures cytosine methylation changes at single-base resolution and can be used to profile cell-free DNA (cfDNA). In plasma, ultrashort single-stranded cfDNA (uscfDNA, ∼50 nt) has been identified together with 167 bp double-stranded mononucleosomal cell-free DNA (mncfDNA). However, the methylation profile of uscfDNA has not been described. Conventional BS-Seq workflows may not be helpful because bisulfite conversion degrades larger DNA into smaller fragments, leading to erroneous categorization as uscfDNA. We describe the '5mCAdpBS-Seq' workflow in which pre-methylated 5mC (5-methylcytosine) single-stranded adapters are ligated to heat-denatured cfDNA before bisulfite conversion. This method retains only DNA fragments that are unaltered by bisulfite treatment, resulting in less biased uscfDNA methylation analysis. Using 5mCAdpBS-Seq, uscfDNA had lower levels of DNA methylation (∼15%) compared to mncfDNA and was enriched in promoters and CpG islands. Hypomethylated uscfDNA fragments were enriched in upstream transcription start sites (TSSs), and the intensity of enrichment was correlated with expressed genes of hemopoietic cells. Using tissue-of-origin deconvolution, we inferred that uscfDNA is derived primarily from eosinophils, neutrophils, and monocytes. As proof-of-principle, we show that characteristics of the methylation profile of uscfDNA can distinguish non-small cell lung carcinoma from non-cancer samples. The 5mCAdpBS-Seq workflow is recommended for any cfDNA methylation-based investigations.

Acute lymphoblastic leukemia (ALL) is the most common cancer in children, yet few environmental risk factors have been identified. We previously found an association between early-life tobacco smoke exposure and frequency of somatic deletions of 8 leukemia driver genes among childhood ALL patients in the California Childhood Leukemia Study. To expand analysis genome-wide and examine potential mechanisms, we conducted tumor whole-genome sequencing in 35 ALL patients, including 18 with high prenatal tobacco exposure and 17 with low exposure as determined by established epigenetic biomarkers. High tobacco exposure patients had significantly more structural variants (P < .001) and deletions (P = .001) genome-wide than low exposure patients. Investigation of off-target RAG recombination revealed that 41% of deletions in the high tobacco exposure patients were putatively RAG-mediated (full RAG motif identified at one or both breakpoints) compared with only 21% in the low exposure group (P = .001). In a multilevel model, deletions in high tobacco exposure patients were 2.44-fold (95% CI:1.13-5.38) more likely to be putatively RAG-mediated than deletions in low exposure patients. No point mutational signatures were associated with prenatal tobacco exposure. Our findings suggest that early-life tobacco smoke exposure may promote leukemogenesis by driving development of somatic deletions in pre-leukemic lymphocytes via off-target RAG recombination.

The cellular components of tumors and their microenvironment play pivotal roles in tumor progression, patient survival, and the response to cancer treatments. Unveiling a comprehensive cellular profile within bulk tumors via single-cell RNA sequencing (scRNA-seq) data is crucial, as it unveils intrinsic tumor cellular traits that elude identification through conventional cancer subtyping methods. Our contribution, scBeacon, is a tool that derives cell-type signatures by integrating and clustering multiple scRNA-seq datasets to extract signatures for deconvolving unrelated tumor datasets on bulk samples. Through the employment of scBeacon on the The Cancer Genome Atlas (TCGA) cohort, we find cellular and molecular attributes within specific tumor categories, many with patient outcome relevance. We developed a tumor cell-type map to visually depict the relationships among TCGA samples based on the cell-type inferences.

Activating signal co-integrator complex 1 (ASCC1) acts with ASCC-ALKBH3 complex in alkylation damage responses. ASCC1 uniquely combines two evolutionarily ancient domains: nucleotide-binding K-Homology (KH) (associated with regulating splicing, transcriptional, and translation) and two-histidine phosphodiesterase (PDE; associated with hydrolysis of cyclic nucleotide phosphate bonds). Germline mutations link loss of ASCC1 function to spinal muscular atrophy with congenital bone fractures 2 (SMABF2). Herein analysis of The Cancer Genome Atlas (TCGA) suggests ASCC1 RNA overexpression in certain tumors correlates with poor survival, Signatures 29 and 3 mutations, and genetic instability markers. We determined crystal structures of Alvinella pompejana (Ap) ASCC1 and Human (Hs) PDE domain revealing high-resolution details and features conserved over 500 million years of evolution. Extending our understanding of the KH domain Gly-X-X-Gly sequence motif, we define a novel structural Helix-Clasp-Helix (HCH) nucleotide binding motif and show ASCC1 sequence-specific binding to CGCG-containing RNA. The V-shaped PDE nucleotide binding channel has two His-Φ-Ser/Thr-Φ (HXT) motifs (Φ being hydrophobic) positioned to initiate cyclic phosphate bond hydrolysis. A conserved atypical active-site histidine torsion angle implies a novel PDE substrate. Flexible active site loop and arginine-rich domain linker appear regulatory. Small-angle X-ray scattering (SAXS) revealed aligned KH-PDE RNA binding sites with limited flexibility in solution. Quantitative evolutionary bioinformatic analyses of disease and cancer-associated mutations support implied functional roles for RNA binding, phosphodiesterase activity, and regulation. Collective results inform ASCC1's roles in transactivation and alkylation damage responses, its targeting by structure-based inhibitors, and how ASCC1 mutations may impact inherited disease and cancer.

7009 Background: The phase 2 CAPTIVATE study evaluated first-line ibrutinib (Ibr) + venetoclax (Ven) for CLL/SLL in 2 cohorts: minimal residual disease (MRD)-guided randomized discontinuation (MRD cohort) and Fixed Duration (FD cohort). Ibr±Ven retreatment was allowed in patients (pts) who had progressive disease (PD). Here, we report outcomes for pts with high-risk genomic features from the FD cohort and retreatment outcomes in pts from the FD cohort and MRD cohort placebo arm. Methods: Pts aged ≤70 y with previously untreated CLL/SLL without restriction on genomic risk factors received 3 cycles of Ibr, then 12 cycles of Ibr+Ven (Ibr, 420 mg/d orally; Ven, 5-wk ramp up to 400 mg/d orally). On-study retreatment included single-agent Ibr (FD cohort or MRD cohort placebo arm); pts with PD >2 y after end of treatment (EOT) could be retreated with FD Ibr+Ven (FD cohort). Results: In the FD cohort (n=159) with a median follow-up of 61.2 mo (range, 0.8–66.3), 5-y PFS and OS rates (95% CI) were 67% (59–74) and 96% (91–98), respectively. 5-y PFS rates were higher in pts with undetectable MRD at 3 mo after EOT in peripheral blood (83%) or bone marrow (84%) vs those without (48% and 50%, respectively). 5-y PFS rates (95% CI) in pts with genomic risk factors were: del(17p)/mutated TP53 41% (21–59), complex karyotype 57% (37–72), del(11q) 64% (30–85), and unmutated IGHV 68% (50–80) (Table). In total, 18 second malignancies occurred in 13 pts (10 events in 8 pts during FD Ibr+Ven, 6 events in 4 pts after EOT and before retreatment, and 2 events in 2 pts during retreatment). Of 202 pts who completed Ibr+Ven (FD cohort, n=159; MRD cohort placebo arm, n=43), 63 have had PD to date; PD occurred >2 y after EOT in 43/63 pts (68%). 32/63 (51%) pts initiated retreatment with Ibr (n=25) or Ibr+Ven (n=7). With a median time on Ibr retreatment of 21.9 mo (range, 0.03–50.4), ORR was 86% in 22 evaluable pts (best response: 1 CR; 1 nodular PR; 17 PR; 2 SD; 1 PD [Richter transformation]). With a median time on Ibr+Ven retreatment of 13.8 mo (range, 3.7–15.1), ORR was 71% in 7 evaluable pts (best response: 1 CR; 4 PR; 1 PR with lymphocytosis; 1 SD). Conclusions: With up to 5.5 y of follow-up, FD Ibr+Ven continues to provide clinically meaningful PFS in pts with high-risk genomic features, as well as in the overall population. Ibr-based retreatment provides promising responses in pts needing subsequent therapy after the all-oral FD regimen of Ibr+Ven. Clinical trial information: NCT02910583 . [Table: see text]

Intratumor heterogeneity underlies cancer evolution and treatment resistance, but targetable mechanisms driving intratumor heterogeneity are poorly understood. Meningiomas are the most common primary intracranial tumors and are resistant to all medical therapies, and high-grade meningiomas have significant intratumor heterogeneity. Here we use spatial approaches to identify genomic, biochemical and cellular mechanisms linking intratumor heterogeneity to the molecular, temporal and spatial evolution of high-grade meningiomas. We show that divergent intratumor gene and protein expression programs distinguish high-grade meningiomas that are otherwise grouped together by current classification systems. Analyses of matched pairs of primary and recurrent meningiomas reveal spatial expansion of subclonal copy number variants associated with treatment resistance. Multiplexed sequential immunofluorescence and deconvolution of meningioma spatial transcriptomes using cell types from single-cell RNA sequencing show decreased immune infiltration, decreased MAPK signaling, increased PI3K-AKT signaling and increased cell proliferation, which are associated with meningioma recurrence. To translate these findings to preclinical models, we use CRISPR interference and lineage tracing approaches to identify combination therapies that target intratumor heterogeneity in meningioma cell co-cultures.

Glioblastoma is a clinically and molecularly heterogeneous disease, and new predictive biomarkers are needed to identify those patients most likely to respond to specific treatments. Through prospective genomic profiling of 459 consecutive primary treatment-naïve IDH-wildtype glioblastomas in adults, we identified a unique subgroup (2%, 9/459) defined by somatic hypermutation and DNA replication repair deficiency due to biallelic inactivation of a canonical mismatch repair gene. The deleterious mutations in mismatch repair genes were often present in the germline in the heterozygous state with somatic inactivation of the remaining allele, consistent with glioblastomas arising due to underlying Lynch syndrome. A subset of tumors had accompanying proofreading domain mutations in the DNA polymerase POLE and resultant "ultrahypermutation". The median age at diagnosis was 50 years (range 27-78), compared with 63 years for the other 450 patients with conventional glioblastoma (p

Plasticity in gene expression allows bacteria to adapt to diverse environments. This is particularly relevant in the dynamic niche of the human intestinal tract; however, transcriptional networks remain largely unknown for gut-resident bacteria. Here we apply differential RNA sequencing (RNA-seq) and conventional RNA-seq to the model gut bacterium Bacteroides thetaiotaomicron to map transcriptional units and profile their expression levels across 15 in vivo-relevant growth conditions. We infer stress- and carbon source-specific transcriptional regulons and expand the annotation of small RNAs (sRNAs). Integrating this expression atlas with published transposon mutant fitness data, we predict conditionally important sRNAs. These include MasB, which downregulates tetracycline tolerance. Using MS2 affinity purification and RNA-seq, we identify a putative MasB target and assess its role in the context of the MasB-associated phenotype. These data-publicly available through the Theta-Base web browser ( http://micromix.helmholtz-hiri.de/bacteroides/ )-constitute a valuable resource for the microbiome community.

IDH1mut gliomas produce high levels of D-2-hydroxyglutarate (D-2-HG), an oncometabolite capable of inhibiting α-ketoglutarate-dependent dioxygenases critical to a range of cellular functions involved in gliomagenesis. IDH1mut gliomas also exhibit slower growth rates and improved treatment sensitivity compared with their IDH1wt counterparts. This study explores the mechanism driving apparent reduced growth in IDH1mut gliomas. Specifically, we investigated the relationship between IDH1mut and the RNA N6-methyladenosine (m6A) demethylases FTO and ALKBH5, and their potential for therapeutic targeting. We investigated the role of D-2-HG and m6A in tumor proliferation/viability using glioma patient tumor samples, patient-derived gliomaspheres, and U87 cells, as well as with mouse intracranial IDH1wt gliomasphere xenografts. Methylation RNA immunoprecipitation sequencing (MeRIP-seq) RNA sequencing was used to identify m6A-enriched transcripts in IDH1mut glioma. We show that IDH1mut production of D-2-HG is capable of reducing glioma cell growth via inhibition of the m6A epitranscriptomic regulator, FTO, with resultant m6A hypermethylation of a set of mRNA transcripts. On the basis of unbiased MeRIP-seq epitranscriptomic profiling, we identify ATF5 as a hypermethylated, downregulated transcript that potentially contributes to increased apoptosis. We further demonstrate how targeting this pathway genetically and pharmacologically reduces the proliferative potential of malignant IDH1wt gliomas, both in vitro and in vivo. Our work provides evidence that selective inhibition of the m6A epitranscriptomic regulator FTO attenuates growth in IDH1wt glioma, recapitulating the clinically favorable growth phenotype seen in the IDH1mut subtype.SignificanceWe show that IDH1mut-generated D-2-HG can reduce glioma growth via inhibition of the m6A demethylase, FTO. FTO inhibition represents a potential therapeutic target for IDH1wt gliomas and possibly in conjunction with IDH1mut inhibitors for the treatment of IDH1mut glioma. Future studies are necessary to demonstrate the role of ATF5 downregulation in the indolent phenotype of IDH1mut gliomas, as well as to identify other involved gene transcripts deregulated by m6A hypermethylation.

The maintenance of DNA sequence integrity is critical to avoid accumulation of cancer-causing mutations. Inactivation of DNA Mismatch Repair (MMR) genes (e.g., MLH1 and MSH2) is common among many cancers, including colorectal cancer (CRC) and is the driver of classic microsatellite instability (MSI) in tumors. Somatic MSH3 alterations have been linked to a specific form of MSI called elevated microsatellite alterations at selected tetranucleotide repeats (EMAST) that is associated with patient poor prognosis and elevated among African American (AA) rectal cancer patients. Genetic variants of MSH3 and their pathogenicity vary among different populations, such as among AA, which are not well-represented in publicly available databases. Targeted exome sequencing of MSH3 among AA CRC samples followed by computational bioinformatic pipeline and molecular dynamic simulation analysis approach confirmed six identified MSH3 variants (c.G1237A, c.C2759T, c.G1397A, c.G2926A, c.C3028T, c.G3241A) that corresponded to MSH3 amino-acid changes (p.E413K; p.S466N; p.S920F; p.E976K; p.H1010Y; p.E1081K). All identified MSH3 variants were non-synonymous, novel, pathogenic, and show loss or gain of hydrogen bonding, ionic bonding, hydrophobic bonding, and disulfide bonding and have a deleterious effect on the structure of MSH3 protein. Some variants were located within the ATPase site of MSH3, affecting ATP hydrolysis that is critical for MSH3's function. Other variants were in the MSH3-MSH2 interacting domain, important for MSH3's binding to MSH2. Overall, our data suggest that these variants among AA CRC patients affect the function of MSH3 making them pathogenic and likely contributing to the development or advancement of CRC among AA. Further clarifying functional studies will be necessary to fully understand the impact of these variants on MSH3 function and CRC development in AA patients.

PurposeModels to study metastatic disease in rare cancers are needed to advance preclinical therapeutics and to gain insight into disease biology. Osteosarcoma is a rare cancer with a complex genomic landscape in which outcomes for patients with metastatic disease are poor. As osteosarcoma genomes are highly heterogeneous, multiple models are needed to fully elucidate key aspects of disease biology and to recapitulate clinically relevant phenotypes.Experimental designMatched patient samples, patient-derived xenografts (PDX), and PDX-derived cell lines were comprehensively evaluated using whole-genome sequencing and RNA sequencing. The in vivo metastatic phenotype of the PDX-derived cell lines was characterized in both an intravenous and an orthotopic murine model. As a proof-of-concept study, we tested the preclinical effectiveness of a cyclin-dependent kinase inhibitor on the growth of metastatic tumors in an orthotopic amputation model.ResultsPDXs and PDX-derived cell lines largely maintained the expression profiles of the patient from which they were derived despite the emergence of whole-genome duplication in a subset of cell lines. The cell lines were heterogeneous in their metastatic capacity, and heterogeneous tissue tropism was observed in both intravenous and orthotopic models. Single-agent dinaciclib was effective at dramatically reducing the metastatic burden.ConclusionsThe variation in metastasis predilection sites between osteosarcoma PDX-derived cell lines demonstrates their ability to recapitulate the spectrum of the disease observed in patients. We describe here a panel of new osteosarcoma PDX-derived cell lines that we believe will be of wide use to the osteosarcoma research community.

Cutaneous melanomas are clinically and histologically heterogeneous. Most display activating mutations in Braf or Nras and complete loss of function of one or more tumor suppressor genes. Mouse models that replicate such mutations produce fast-growing, pigmented tumors. However, mice that combine Braf activation with only heterozygous loss of Pten also produce tumors and, as we show here, in an Albino background this occurs even with Braf activation alone. Such tumors arise rarely, grow slowly, and express low levels of pigmentation genes. The timing of their appearance was consistent with a single step stochastic event, but no evidence could be found that it required de novo mutation, suggesting instead the involvement of an epigenetic transition. Single-cell transcriptomic analysis revealed such tumors to be heterogeneous, including a minor cell type we term LNM ( L ow-pigment, N eural- and extracellular M atrix-signature) that displays gene expression resembling "neural crest"-like cell subsets detected in the fast-growing tumors of more heavily-mutated mice, as well as in human biopsy and xenograft samples. We provide evidence that LNM cells pre-exist in normal skin, are expanded by Braf activation, can transition into malignant cells, and persist with malignant cells through multiple rounds of transplantation. We discuss the possibility that LNM cells not only serve as a pre-malignant state in the production of some melanomas, but also as an important intermediate in the development of drug resistance.

The UCSC Genome Browser (https://genome.ucsc.edu) is a web-based genomic visualization and analysis tool that serves data to over 7,000 distinct users per day worldwide. It provides annotation data on thousands of genome assemblies, ranging from human to SARS-CoV2. This year, we have introduced new data from the Human Pangenome Reference Consortium and on viral genomes including SARS-CoV2. We have added 1,200 new genomes to our GenArk genome system, increasing the overall diversity of our genomic representation. We have added support for nine new user-contributed track hubs to our public hub system. Additionally, we have released 29 new tracks on the human genome and 11 new tracks on the mouse genome. Collectively, these new features expand both the breadth and depth of the genomic knowledge that we share publicly with users worldwide.

BackgroundMetastatic relapse of prostate cancer after radiotherapy is a significant cause of prostate cancer-related morbidity and mortality. PLOD2 is a mediator of invasion and metastasis that we identified as being upregulated in our highly aggressive radiorecurrent prostate cancer cell line.MethodsPatient dataset analysis was conducted using a variety of prostate cancer cohorts. Prostate cancer cell lines were treated with siRNA, or the drug PX-478 prior to in vitro invasion, migration, or in vivo chick embryo (CAM) extravasation assay. Protein levels were detected by western blot. For RNA analysis, RNA sequencing was conducted on PLOD2 knockdown cells and validated by qRT-PCR.ResultsPLOD2 is a negative prognostic factor associated with biochemical relapse, driving invasion, migration, and extravasation in radiorecurrent prostate cancer. Mechanistically, HIF1α upregulation drives PLOD2 expression in our radiorecurrent prostate cancer cells, which is effectively inhibited by HIF1α inhibitor PX-478 to reduce invasion, migration, and extravasation. Finally, the long non-coding RNA LNCSRLR acts as a promoter of invasion downstream of PLOD2.ConclusionsTogether, our results demonstrate for the first time the role of PLOD2 in radiorecurrent prostate cancer invasiveness, and point towards its potential as a therapeutic target to reduce metastasis and improve survival outcomes in prostate cancer patients.

Chemical probes interrogate disease mechanisms at the molecular level by linking genetic changes to observable traits. However, comprehensive chemical screens in diverse biological models are impractical. To address this challenge, we develop ChemProbe, a model that predicts cellular sensitivity to hundreds of molecular probes and drugs by learning to combine transcriptomes and chemical structures. Using ChemProbe, we infer the chemical sensitivity of cancer cell lines and tumor samples and analyze how the model makes predictions. We retrospectively evaluate drug response predictions for precision breast cancer treatment and prospectively validate chemical sensitivity predictions in new cellular models, including a genetically modified cell line. Our model interpretation analysis identifies transcriptome features reflecting compound targets and protein network modules, identifying genes that drive ferroptosis. ChemProbe is an interpretable in silico screening tool that allows researchers to measure cellular response to diverse compounds, facilitating research into molecular mechanisms of chemical sensitivity.

BackgroundEpigenetic changes link medical, social, and environmental factors with cardiovascular and kidney disease and, more recently, with cancer. The mechanistic link between metabolic health and epigenetic changes is only starting to be investigated. In our in vitro and in vivo studies, we performed a broad analysis of the link between hyperinsulinemia and chromatin acetylation; our top "hit" was chromatin opening at H3K9ac.MethodsBuilding on our published preclinical studies, here, we performed a detailed analysis of the link between insulin resistance, chromatin acetylation, and inflammation using an initial test set of 28 women and validation sets of 245, 22, and 53 women.ResultsChIP-seq identified chromatin acetylation and opening at the genes coding for TNFα and IL6 in insulin-resistant women. Pathway analysis identified inflammatory response genes, NFκB/TNFα-signaling, reactome cytokine signaling, innate immunity, and senescence. Consistent with this finding, flow cytometry identified increased senescent circulating peripheral T-cells. DNA methylation analysis identified evidence of accelerated aging in insulin-resistant vs. metabolically healthy women.ConclusionsThis study shows that insulin-resistant women have increased chromatin acetylation/opening, inflammation, and, perhaps, accelerated aging. Given the role that inflammation plays in cancer initiation and progression, these studies provide a potential mechanistic link between insulin resistance and cancer.

Tumors may contain billions of cells, including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that are consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.

Acral melanoma is an aggressive type of melanoma with unknown origins. It is the most common type of melanoma in individuals with dark skin and is notoriously challenging to treat. We examine exome sequencing data of 139 tissue samples, spanning different progression stages, from 37 patients. We find that 78.4% of the melanomas display clustered copy number transitions with focal amplifications, recurring predominantly on chromosomes 5, 11, 12, and 22. These complex genomic aberrations are typically shared across all progression stages of individual patients. TERT activating alterations also arise early, whereas MAP-kinase pathway mutations appear later, an inverted order compared to the canonical evolution. The punctuated formation of complex aberrations and early TERT activation suggest a unique mutational mechanism that initiates acral melanoma. The marked intratumoral heterogeneity, especially concerning MAP-kinase pathway mutations, may partly explain the limited success of therapies for this melanoma subtype.

DNA methyltransferases DNMT3A- and DNMT3B-mediated DNA methylation critically regulate epigenomic and transcriptomic patterning during development. The hotspot DNMT3A mutations at the site of Arg822 (R882) promote polymerization, leading to aberrant DNA methylation that may contribute to the pathogenesis of acute myeloid leukemia (AML). However, the molecular basis underlying the mutation-induced functional misregulation of DNMT3A remains unclear. Here, we report the crystal structures of the DNMT3A methyltransferase domain, revealing a molecular basis for its oligomerization behavior distinct to DNMT3B, and the enhanced intermolecular contacts caused by the R882H or R882C mutation. Our biochemical, cellular, and genomic DNA methylation analyses demonstrate that introducing the DNMT3B-converting mutations inhibits the R882H-/R882C-triggered DNMT3A polymerization and enhances substrate access, thereby eliminating the dominant-negative effect of the DNMT3A R882 mutations in cells. Together, this study provides mechanistic insights into DNMT3A R882 mutations-triggered aberrant oligomerization and DNA hypomethylation in AML, with important implications in cancer therapy.

Understanding the function of rare non-coding variants represents a significant challenge. Using MapUTR, a screening method, we studied the function of rare 3' UTR variants affecting mRNA abundance post-transcriptionally. Among 17,301 rare gnomAD variants, an average of 24.5% were functional, with 70% in cancer-related genes, many in critical cancer pathways. This observation motivated an interrogation of 11,929 somatic mutations, uncovering 3928 (33%) functional mutations in 155 cancer driver genes. Functional MapUTR variants were enriched in microRNA- or protein-binding sites and may underlie outlier gene expression in tumors. Further, we introduce untranslated tumor mutational burden (uTMB), a metric reflecting the amount of somatic functional MapUTR variants of a tumor and show its potential in predicting patient survival. Through prime editing, we characterized three variants in cancer-relevant genes (MFN2, FOSL2, and IRAK1), demonstrating their cancer-driving potential. Our study elucidates the function of tens of thousands of non-coding variants, nominates non-coding cancer driver mutations, and demonstrates their potential contributions to cancer.

In clinical oncology, cell-free DNA (cfDNA) has shown immense potential in its ability to noninvasively detect cancer at various stages and monitor the progression of therapy. Despite the rapid improvements in cfDNA liquid biopsy approaches, achieving the required sensitivity to detect rare tumor-derived cfDNA still remains a challenge. For next-generation sequencing, the perceived presentation of cfDNA is strongly linked to the extraction and library preparation protocols. Conventional double-stranded DNA library preparation (dsDNA-LP) focuses on assessing ~167bp double-stranded mononucleosomal (mncfDNA) and its other oligonucleosomal cell-free DNA counterparts in plasma. However, dsDNA-LP methods fail to include short, single-stranded, or nicked DNA in the final library preparation, biasing the representation of the actual cfDNA populations in plasma. The emergence of single-stranded library preparation (ssDNA-LP) strategies over the past decade has now allowed these other populations of cfDNA to be studied from plasma. With the use of ssDNA-LP, single-stranded, nicked, and ultrashort cfDNA can be comprehensively assessed for its molecular characteristics and clinical potential. In this review, we overview the current literature on applications of ssDNA-LP on plasma cfDNA from a potential cancer liquid biopsy perspective. To this end, we discuss the molecular principles of single-stranded DNA adapter ligation, how library preparation contributes to the understanding of native cfDNA characteristics, and the potential for ssDNA-LP to improve the sensitivity of circulating tumor DNA detection. Additionally, we review the current literature on the newly reported species of plasma ultrashort single-stranded cell-free DNA plasma, which appear biologically distinct from mncfDNA. We conclude with a discussion of future perspectives of ssDNA-LP for liquid biopsy endeavors.

Despite advancements in cancer immunotherapy, solid tumors remain formidable challenges. In glioma, profound inter- and intra-tumoral heterogeneity of antigen landscape hampers therapeutic development. Therefore, it is critical to consider alternative sources to expand the repertoire of targetable (neo-)antigens and improve therapeutic outcomes. Accumulating evidence suggests that tumor-specific alternative splicing (AS) could be an untapped reservoir of antigens. In this study, we investigated tumor-specific AS events in glioma, focusing on those predicted to generate major histocompatibility complex (MHC)-presentation-independent, cell-surface antigens that could be targeted by antibodies and chimeric antigen receptor-T cells. We systematically analyzed bulk RNA-sequencing datasets comparing 429 tumor samples (from The Cancer Genome Atlas) and 9166 normal tissue samples (from the Genotype-Tissue Expression project), and identified 13 AS events in 7 genes predicted to be expressed in more than 10% of the patients, including PTPRZ1 and BCAN, which were corroborated by an external RNA-sequencing dataset. Subsequently, we validated our predictions and elucidated the complexity of the isoforms using full-length transcript amplicon sequencing on patient-derived glioblastoma cells. However, analyses of the RNA-sequencing datasets of spatially mapped and longitudinally collected clinical tumor samples unveiled remarkable spatiotemporal heterogeneity of the candidate AS events. Furthermore, proteomics analysis did not reveal any peptide spectra matching the putative antigens. Our investigation illustrated the diverse characteristics of the tumor-specific AS events and the challenges of antigen exploration due to their notable spatiotemporal heterogeneity and elusive nature at the protein levels. Redirecting future efforts toward intracellular, MHC-presented antigens could offer a more viable avenue.

Clinical management of non-small cell lung cancer (NSCLC) requires accurate identification of tumor-specific genetic alterations to inform treatment options. Historically, providers have relied on single-gene testing (SGT) for actionable variants due to a perception of cost-effectiveness and/or efficient turnaround time compared to next-generation sequencing (NGS). However, not all actionable variants may be evaluated through SGT modalities, and an SGT approach can exhaust valuable tissue needed for more comprehensive analyses. In contrast, comprehensive genomic profiling (CGP) tests employ NGS to sequence megabases of DNA and RNA to evaluate all relevant molecular alterations, providing a broader genetic profile to identify actionable alterations that SGT may not accurately or efficiently assess. Here, we briefly describe four cases from a large reference laboratory in which actionable alterations were identified by CGP but not SGT. The discussion highlights the utility and advantages of using CGP to provide complete and timely treatment options and clinical trial opportunities for patients with NSCLC. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is the leading cause of cancer-related mortality among women, and hormone receptor (HR)-positive subtype makes up the majority of all cases. The standard of care in HR+/HER2− metastatic BC (MBC) is endocrine therapy (ET) plus a CDK4/6 inhibitor (CDK4/6i). ESR1 mutations could impair the clinical efficacy of the ETs. Similarly, PIK3CA mutations may serve as a negative prognostic marker. Furthermore, MBC is challenging to treat despite new drug approvals. Our patient received multiple lines of ET ± CDK4/6i and chemotherapy but persistently progressed after each or stopped the treatment due to adverse events. Here we showed for the first time that an all-oral combination of elacestrant plus alpelisib was feasible, tolerable, and clinically active in an ESR1 and PIK3CA co-mutated and heavily pretreated patient. We achieved a remarkable response in the metastatic lesions with minor toxicity issues. This case highlights the importance of utilizing up-to-date therapeutic agents and reactive decision-making during personalized cancer treatment. [ABSTRACT FROM AUTHOR]

Objectives: The primary goal of this research is to develop treatment-related genomic predictive markers for non-small cell lung cancer by integrating various machine learning algorithms that recommends near-optimal individualized patient treatment for chemotherapy in an effort to maximize efficacy or minimize treatment-related toxicity. This research can contribute toward developing a more refined, accurate and effective therapy accounting for specific patient needs. Methods: To accomplish our research goal, we implement ensemble learning algorithms, bagging with regularized Cox regression models and nonparametric tree-based models via Random Survival Forests. A comprehensive meta-database was compiled from the NCBI Gene Expression Omnibus data repository for lung cancer patients to capture and utilize complex genomic patterns that can predict treatment outcomes more accurately. Results: The developed novel prediction algorithm demonstrates the ability to support complex clinical decision-making processes in the treatment of NSCLC. It effectively addresses patient heterogeneity, offering predictions that are both refined and personalized in improving the precision of chemotherapy regimens prescribed to the eligible patients. Conclusion: This research should contribute substantial advancement of cancer treatments by improving the accuracy and efficacy of chemotherapy treatments for a targeted group of patients who need the right treatment. The integration of complex machine learning techniques with genomic data holds substantial potential to transform current cancer treatment paradigms by providing robust support in clinical decision-making. [ABSTRACT FROM AUTHOR]

Simple Summary: The OncoIndx® platform is an NGS assay designed and developed to identify critical mutations that help in therapeutic decision-making. The OncoIndx® panel targets major exons and a few selected introns of 1080 cancer-associated and actionable genes. The test analyzes complex biomarkers such as single nucleotide variants (SNVs), copy number alterations (CNAs), specific gene fusions, and many more. This study validates the overall sensitivity and efficiency of the test using standard references, clinical samples, and U.S. Food and Drug Administration (FDA)-approved cross-laboratory samples. The ultimate goal of this research is to benchmark the assay against the current guidelines and increase the reliability of the test, thus increasing the confidence of medical professionals for better personalized therapeutic intervention. Comprehensive next-generation sequencing (NGS) assays enable the identification of clinically relevant mutations, enhancing the capability for targeted therapeutic interventions. In addition, genomic alterations driving the oncogenic roadmap and leading to resistance mechanisms are reshaping precision oncology. We report the workflow and clinical and technical validation of the OncoIndx® NGS platform—a comprehensive genomic profiling (CGP)-based assay for pan-cancer investigation. We evaluated the concordance between the OncoIndx® test findings and clinically established hotspot detection using SeraSeq reference standards. OncoIndx is a hybridization capture-based NGS assay for the targeted deep sequencing of all exons and selected introns of 1080 cancer-related genes. We show the outcome in the form of tier I and tier II single nucleotide variants (SNVs), copy number alterations (CNAs), and specific gene fusions. OncoIndx® also informs genome-wide tumor mutational burden (TMB), microsatellite instability (MSI), homologous recombination deficiency (HRD), and genomic loss of heterozygosity (gLOH). A total of 63 samples were utilized for validation with reference standards, clinical samples, and orthogonal assessment for genomic alterations. In addition, 49 cross-laboratory samples were validated for microsatellite instability (MSI), and for the tumor mutation burden (TMB), 18 samples as reference standards, 6 cross-laboratory samples, and 29 TCGA samples were utilized. We show a maximum clinical sensitivity of 98% and a positive predictive value (PPV) of 100% for the clinically actionable genomic variants detected by the assay. In addition, we demonstrate analytical validation with the performance of the assay, limit of detection (LoD), precision, and orthogonal concordance for various types of SVs, CNAs, genomic rearrangements, and complex biomarkers like TMB, MSI, and HRD. The assay offers reliable genomic predictions with the high-precision detection of actionable variants, validated by established reference standards. [ABSTRACT FROM AUTHOR]

Background: Comprehensive genomic profiling (CGP) can aid the discovery of clinically useful, candidate antitumor agents; however, the variant annotations sometimes differ among the various types of CGP tests as well as the public database. The aim of this study is to clarify the genomic landscape of evaluating detected variants in patients with a malignant solid tumor. Methods: The present, cross-sectional study used data from 57,084 patients with a malignant solid tumor who underwent CGP at the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) between June 1, 2019 and August 18, 2023. The pathogenicity of the variants was annotated using public databases. Results: As a result of re-annotation of the detected variants, 20.1% were pathogenic and 1.4% were benign. The mean number of pathogenic variants was 4.30 (95% confidence interval: 4.27–4.32) per patient. Of the entire cohort, 5.7% had no pathogenic variant. The co-occurrence of the genes depended on the tumor type. Germline findings were detected in 6.2%, 8.8%, and 15.8% of the patients using a tumor/normal panel, tumor-only panel, and liquid panel, respectively, with the most common gene being BRCA2 followed by TP53 and BRCA1. Conclusions: The detected variants should be re-annotated because several benign variants or variants of unknown significance were included in the CGP, and the genomic landscape derived from these results will help researchers and physicians interpret the results of CGP tests. The method of extracting presumptive, germline, pathogenic variants from patients using a tumor-only panel or circulating tumor DNA panel requires improvement. [ABSTRACT FROM AUTHOR]

This study investigates the impact of Hashimoto’s thyroiditis (HT), an autoimmune disorder, on the papillary thyroid cancer (PTC) microenvironment using a dataset of 140,456 cells from 11 patients. By comparing PTC cases with and without HT, we identify HT-specific cell populations (HASCs) and their role in creating a TSH-suppressive environment via mTE3, nTE0, and nTE2 thyroid cells. These cells facilitate intricate immune–stromal communication through the MIF–(CD74+CXCR4) axis, emphasizing immune regulation in the TSH context. In the realm of personalized medicine, our HASC-focused analysis within the TCGA-THCA dataset validates the utility of HASC profiling for guiding tailored therapies. Moreover, we introduce a novel, objective method to determine K- means clustering coefficients in copy number variation inference from bulk RNA- seq data, mitigating the arbitrariness in conventional coefficient selection. Collectively, our research presents a detailed single-cell atlas illustrating HT– PTC interactions, deepening our understanding of HT’s modulatory effects on PTC microenvironments. It contributes to our understanding of autoimmunity– carcinogenesis dynamics and charts a course for discovering new therapeutic targets in PTC, advancing cancer genomics and immunotherapy research. [ABSTRACT FROM AUTHOR]

Circular extrachromosomal DNA (ecDNA) in patient tumors is an important driver of oncogenic gene expression, evolution of drug resistance and poor patient outcomes. Applying computational methods for the detection and reconstruction of ecDNA across a retrospective cohort of 481 medulloblastoma tumors from 465 patients, we identify circular ecDNA in 82 patients (18%). Patients with ecDNA-positive medulloblastoma were more than twice as likely to relapse and three times as likely to die within 5 years of diagnosis. A subset of tumors harbored multiple ecDNA lineages, each containing distinct amplified oncogenes. Multimodal sequencing, imaging and CRISPR inhibition experiments in medulloblastoma models reveal intratumoral heterogeneity of ecDNA copy number per cell and frequent putative 'enhancer rewiring' events on ecDNA. This study reveals the frequency and diversity of ecDNA in medulloblastoma, stratified into molecular subgroups, and suggests copy number heterogeneity and enhancer rewiring as oncogenic features of ecDNA.

A greater understanding of molecular, cellular, and immunological changes during the early stages of lung adenocarcinoma development could improve diagnostic and therapeutic approaches in patients with pulmonary nodules at risk for lung cancer. To elucidate the immunopathogenesis of early lung tumorigenesis, we evaluated surgically resected pulmonary nodules representing the spectrum of early lung adenocarcinoma as well as associated normal lung tissues using single-cell RNA sequencing and validated the results by flow cytometry and multiplex immunofluorescence (MIF). Single-cell transcriptomics revealed a significant decrease in gene expression associated with cytolytic activities of tumor-infiltrating natural killer and natural killer T cells. This was accompanied by a reduction in effector T cells and an increase of CD4+ regulatory T cells (Treg) in subsolid nodules. An independent set of resected pulmonary nodules consisting of both adenocarcinomas and associated premalignant lesions corroborated the early increment of Tregs in premalignant lesions compared with the associated normal lung tissues by MIF. Gene expression analysis indicated that cancer-associated alveolar type 2 cells and fibroblasts may contribute to the deregulation of the extracellular matrix, potentially affecting immune infiltration in subsolid nodules through ligand-receptor interactions. These findings suggest that there is a suppression of immune surveillance across the spectrum of early-stage lung adenocarcinoma.SignificanceAnalysis of a spectrum of subsolid pulmonary nodules by single-cell RNA sequencing provides insights into the immune regulation and cell-cell interactions in the tumor microenvironment during early lung tumor development.

Cell-cell interactions instruct cell fate and function. These interactions are hijacked to promote cancer development. Single-cell transcriptomics and spatial transcriptomics have become powerful new tools for researchers to profile the transcriptional landscape of cancer at unparalleled genetic depth. In this review, we discuss the rapidly growing array of computational tools to infer cell-cell interactions from non-spatial single-cell RNA-sequencing and the limited but growing number of methods for spatial transcriptomics data. Downstream analyses of these computational tools and applications to cancer studies are highlighted. We finish by suggesting several directions for further extensions that anticipate the increasing availability of multi-omics cancer data.

BackgroundAlthough recent sequencing studies have revealed that 10% of childhood gliomas are caused by rare germline mutations, the role of common variants is undetermined and no genome-wide significant risk loci for pediatric central nervous system tumors have been identified to date.MethodsMeta-analysis of 3 population-based genome-wide association studies comprising 4069 children with glioma and 8778 controls of multiple genetic ancestries. Replication was performed in a separate case-control cohort. Quantitative trait loci analyses and a transcriptome-wide association study were conducted to assess possible links with brain tissue expression across 18 628 genes.ResultsCommon variants in CDKN2B-AS1 at 9p21.3 were significantly associated with astrocytoma, the most common subtype of glioma in children (rs573687, P-value of 6.974e-10, OR 1.273, 95% CI 1.179-1.374). The association was driven by low-grade astrocytoma (P-value of 3.815e-9) and exhibited unidirectional effects across all 6 genetic ancestries. For glioma overall, the association approached genome-wide significance (rs3731239, P-value of 5.411e-8), while no significant association was observed for high-grade tumors. Predicted decreased brain tissue expression of CDKN2B was significantly associated with astrocytoma (P-value of 8.090e-8).ConclusionsIn this population-based genome-wide association study meta-analysis, we identify and replicate 9p21.3 (CDKN2B-AS1) as a risk locus for childhood astrocytoma, thereby establishing the first genome-wide significant evidence of common variant predisposition in pediatric neuro-oncology. We furthermore provide a functional basis for the association by showing a possible link to decreased brain tissue CDKN2B expression and substantiate that genetic susceptibility differs between low- and high-grade astrocytoma.

In comparison with responses in recurrent glioblastoma (rGBM), the intracranial response of brain metastases (BrM) to immune checkpoint blockade (ICB) is less well studied. Here, we present an integrated single-cell RNA-Seq (scRNA-Seq) study of 19 ICB-naive and 9 ICB-treated BrM samples from our own and published data sets. We compared them with our previously published scRNA-Seq data from rGBM and found that ICB led to more prominent T cell infiltration into BrM than rGBM. These BrM-infiltrating T cells exhibited a tumor-specific phenotype and displayed greater activated/exhausted features. We also used multiplex immunofluorescence and spatial transcriptomics to reveal that ICB reduced a distinct CD206+ macrophage population in the perivascular space, which may modulate T cell entry into BrM. Furthermore, we identified a subset of progenitor exhausted T cells that correlated with longer overall survival in BrM patients. Our study provides a comprehensive immune cellular landscape of ICB's effect on metastatic brain tumors and offers insights into potential strategies for improving ICB efficacy for brain tumor patients.

PurposeTo report a large uveal melanoma with extra-scleral extension which underwent spontaneous infarction and its unique molecular signature profile.ObservationsAn 81-year-old female presented with a blind, painful eye. Intraocular pressure was 48 mm Hg. There was a large subconjunctival melanotic mass overlying a choroidal melanoma with anterior extension involving the ciliary body and the iridocorneal angle and iris. Ultrasonography confirmed a dome-shaped anterior cilio-choroidal mass with extra-scleral extension. The patient underwent enucleation and pathologic evaluation confirmed cilio-choroidal melanoma. The posterior half of the tumor involving the ciliary body and the extra-scleral component were spontaneously infarcted and were composed of large melanophages. Next-generation sequencing demonstrated a splice site mutation in PBRM1 and whole-genome doubling in addition to a GNAQ hotspot mutation, chromosome 3 loss and 8q gain.Conclusions and importanceThis case of a large, auto-infarcted uveal melanoma demonstrates a PBRM1 mutation and whole-genome doubling.

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Abstract Background Health disparities have been highlighted among patient with prostate adenocarcinoma (PRAD) due to ethnicity. Mexican men present a more aggressive disease than other patients resulting in less favorable treatment outcome. We aimed to identify the mutational landscape which could help to reduce the health disparities among minority groups and generate the first genomics exploratory study of PRAD in Mexican patients. Methods Paraffin-embedded formalin-fixed tumoral tissue from 20 Mexican patients with early-stage PRAD treated at The Instituto Nacional de Cancerología, Mexico City from 2017 to 2019 were analyzed. Tumoral DNA was prepared for whole exome sequencing, the resulting files were mapped against h19 using BWA-MEM. Strelka2 and Lancet packages were used to identify single nucleotide variants (SNV) and insertions or deletions. FACETS was used to determine somatic copy number alterations (SCNA). Cancer Genome Interpreter web interface was used to determine the clinical relevance of variants. Results Patients were in an early clinical stage and had a mean age of 59.55 years (standard deviation [SD]: 7.1 years) with 90% of them having a Gleason Score of 7. Follow-up time was 48.50 months (SD: 32.77) with recurrences and progression in 30% and 15% of the patients, respectively. NUP98 (20%), CSMD3 (15%) and FAT1 (15%) were the genes most frequently affected by SNV; ARAF (75%) and ZNF419 (70%) were the most frequently affected by losses and gains SNCA’s. One quarter of the patients had mutations useful as biomarkers for the use of PARP inhibitors, they comprise mutations in BRCA, RAD54L and ATM. SBS05, DBS03 and ID08 were the most common mutational signatures present in this cohort. No associations with recurrence or progression were identified. Conclusions This pilot study reveals the mutational landscape of early-stage prostate adenocarcinoma in Mexican men, providing a first approach to understand the mutational patterns and actionable mutations in early prostate cancer can inform personalized treatment approaches and reduce the underrepresentation in genomic cancer studies.

Background: Health disparities have been highlighted among patient with prostate adenocarcinoma (PRAD) due to ethnicity. Mexican men present a more aggressive disease than other patients resulting in less favorable treatment outcome. We aimed to identify the mutational landscape which could help to reduce the health disparities among minority groups and generate the first genomics exploratory study of PRAD in Mexican patients. Methods: Paraffin-embedded formalin-fixed tumoral tissue from 20 Mexican patients with early-stage PRAD treated at The Instituto Nacional de Cancerología, Mexico City from 2017 to 2019 were analyzed. Tumoral DNA was prepared for whole exome sequencing, the resulting files were mapped against h19 using BWA-MEM. Strelka2 and Lancet packages were used to identify single nucleotide variants (SNV) and insertions or deletions. FACETS was used to determine somatic copy number alterations (SCNA). Cancer Genome Interpreter web interface was used to determine the clinical relevance of variants. Results: Patients were in an early clinical stage and had a mean age of 59.55 years (standard deviation [SD]: 7.1 years) with 90% of them having a Gleason Score of 7. Follow-up time was 48.50 months (SD: 32.77) with recurrences and progression in 30% and 15% of the patients, respectively. NUP98 (20%), CSMD3 (15%) and FAT1 (15%) were the genes most frequently affected by SNV; ARAF (75%) and ZNF419 (70%) were the most frequently affected by losses and gains SNCA's. One quarter of the patients had mutations useful as biomarkers for the use of PARP inhibitors, they comprise mutations in BRCA, RAD54L and ATM. SBS05, DBS03 and ID08 were the most common mutational signatures present in this cohort. No associations with recurrence or progression were identified. Conclusions: This pilot study reveals the mutational landscape of early-stage prostate adenocarcinoma in Mexican men, providing a first approach to understand the mutational patterns and actionable mutations in early prostate cancer can inform personalized treatment approaches and reduce the underrepresentation in genomic cancer studies. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, the researchers aimed to improve the prognostic information provided by the standard One-Step Nucleic Acid Amplification (OSNA) assay used to detect breast cancer (BC) metastasis in sentinel lymph nodes (SLNs). They analysed the expression of an immune gene panel in SLNs from Luminal A early-stage BC (cT1-T2 N0) patients, including those with and without subclinical metastasis. The study identified two distinct immune response profiles—one showing an adaptive anti-tumour immune response, and another with a more undifferentiated response. The researchers also identified seven key immunoregulatory genes that could serve as potential targets for immunotherapy. These findings suggest that analysing immune gene expression in SLNs can provide additional prognostic information beyond the OSNA assay results and may help guide personalised treatment approaches for early-stage BC patients. In the management of early-stage breast cancer (BC), lymph nodes (LNs) are typically characterised using the One-Step Nucleic Acid Amplification (OSNA) assay, a standard procedure for assessing subclinical metastasis in sentinel LNs (SLNs). The pivotal role of LNs in coordinating the immune response against BC is often overlooked. Our aim was to improve prognostic information provided by the OSNA assay and explore immune-related gene signatures in SLNs. The expression of an immune gene panel was analysed in SLNs from 32 patients with Luminal A early-stage BC (cT1-T2 N0). Using an unsupervised approach based on these expression values, this study identified two clusters, regardless of the SLN invasion: one evidencing an adaptive anti-tumoral immune response, characterised by an increase in naive B cells, follicular T helper cells, and activated NK cells; and another with a more undifferentiated response, with an increase in the activated-to-resting dendritic cells (DCs) ratio. Through a protein—protein interaction (PPI) network, we identified seven immunoregulatory hub genes: CD80, CD40, TNF, FCGR3A, CD163, FCGR3B, and CCR2. This study shows that, in Luminal A early-stage BC, SLNs gene expression studies enable the identification of distinct immune profiles that may influence prognosis stratification and highlight key genes that could serve as potential targets for immunotherapy. [ABSTRACT FROM AUTHOR]

The rapid advancement of sequencing technologies has led to the identification of numerous mutations in cancer genomes, many of which are variants of unknown significance (VUS). Computational models are increasingly being used to predict the functional impact of these mutations, in both coding and noncoding regions. Integration of these models with emerging genomic datasets will refine our understanding of mutation effects and guide clinical decision making. Future advancements in modeling protein interactions and transcriptional regulation will further enhance our ability to interpret VUS. Periodic incorporation of these developments into VUS reclassification practice has the potential to significantly improve personalized cancer care. [ABSTRACT FROM AUTHOR]