Signatures of mutational processes in human cancer

Quantitative and Systematic NMR Measurements of Sequence-Dependent A-T Hoogsteen Dynamics in the DNA Double Helix

The dynamic properties of DNA depend on the sequence, providing an important source of sequence-specificity in biochemical reactions. However, comprehensively measuring how these dynamics vary with sequence is challenging, especially when they involve lowly populated and short-lived conformational states. Using 1H CEST supplemented by targeted 13C R1ρ NMR experiments, we quantitatively measured Watson-Crick to Hoogsteen dynamics for an A-T base pair in 13 trinucleotide sequence contexts. The Hoogsteen population and exchange rate varied 4-fold and 16-fold, respectively, and were dependent on both the 3'- and 5'-neighbors but only weakly dependent on monovalent ion concentration (25 versus 100 mM NaCl) and pH (6.8 versus 8.0). Flexible TA and CA dinucleotide steps exhibited the highest Hoogsteen populations, and their kinetics rates strongly depended on the 3'-neighbor. In contrast, the stiffer AA and GA steps had the lowest Hoogsteen population, and their kinetics were weakly dependent on the 3'-neighbor. The Hoogsteen lifetime was especially short when G-C neighbors flanked the A-T base pair. Our results uncover a unique conformational basis for sequence-specificity in the DNA double helix and establish the utility of NMR to quantitatively and comprehensively measure sequence-dependent DNA dynamics.

Identification of a novel prognostic and therapeutic prediction model in clear cell renal carcinoma based on Renin-angiotensin system related genes

Background

Clear cell renal cell carcinoma is the most predominant type of renal malignancies, characterized by high aggressiveness and probability of distant metastasis. Renin angiotensin system (RAS) plays a crucial role in maintaining fluid balance within the human body, and its involvement in tumorigenesis is increasingly being uncovered, while its role in ccRCC remains unclear.

Methods

WGCNA was used to identify RAS related genes. Machine learning was applied to screen hub genes for constructing risk model, E-MTAB-1980 dataset was used for external validation. Transwell and CCK8 assays were used to investigate the impact of SLC6A19 to ccRCC cells.

Results

SLC6A19, SLC16A12 and SMIM24 were eventually screened to construct risk model and the predictive efficiency for prognosis was validated by internal and external cohorts. Moreover, the differences were found in pathway enrichment, immune cell infiltration, mutational landscapes and drug prediction between high and low risk groups. Experimental results indicated that SLC6A19 could inhibit invasion and proliferation of ccRCC cells and GSEA pinpointed that SLC6A19 was intimately correlated with fatty acid metabolism and CPT1A.

Conclusion

The risk model based on the three RAS-related genes have a robust ability to predict the prognosis and drug sensitivity of ccRCC patients, further providing a valid instruction for clinical care.

Clinical utility of 'Shaken' biopsies for whole-genome sequencing

AIMS

Whole-genome sequencing (WGS) is beginning to be applied to cancer samples in the clinical setting. This ideally requires high-quality, minimally degraded DNA of high tumour cell content, while retaining sufficient tissue with excellent morphology for histopathological diagnosis and immunohistochemistry. The aim of this study was to investigate alternative ways of handling cancer samples to fulfil both diagnostic and molecular requirements.

METHODS

Ex vivo biopsies were taken to investigate the feasibility of using cancer cells 'shaken' from the surface of a biopsy for WGS, while maintaining the tissue biopsy for histological diagnosis. WGS from the shaken cells was compared with the gold standard of a fresh-frozen (FF) biopsy. The procedure was piloted in the real-world setting for breast cancer samples.

RESULTS

Cells shaken from ex vivo biopsies can yield DNA of sufficient quantity and quality for WGS, while having no discernible impact on quality of tissue morphology. WGS data showed good coverage, comparable variant calls and generally higher tumour content in shaken cell samples compared with the control FF samples. For real-world biopsies, DNA yields were lower, but WGS data were of excellent quality for the cases analysed.

CONCLUSIONS

Shaken biopsy sampling allows genomic sequencing from patients with cancer who may otherwise not receive a genome sequence due to limited sample availability. It represents a way of overcoming the logistics of obtaining and storing FF tissue making it a suitable technique for wider scale implementation in the clinical setting.

The genomic landscape of metastatic clear-cell renal cell carcinoma and its prognostic value: a comprehensive analysis of a large real-world clinico-genomic database

BACKGROUND

Translating findings on the genomic landscape of metastatic clear-cell renal cell carcinoma (mccRCC) into clinical practice remains challenging. A better understanding of the molecular features of mccRCC could identify a prognostic and/or predictive role for ccRCC genomic alterations.

PATIENTS AND METHODS

In this real-world observational study based on the nationwide (US-based) de-identified Flatiron Health-Foundation Medicine, Inc. clinico-genomic database (FH-FMI-CGDB), we investigate the frequency and co-occurrence of genomic alterations in mccRCC patients and assess their prognostic role. Patients (n = 858) were adults diagnosed with mccRCC, with FH electronic health records between 2011 and 2022.

RESULTS

The top 10 mutated genes were VHL (73.9%), PBRM1 (42.4%), SETD2 (25.3%), CDKN2A (20.0%), BAP1 (16.4%), CDKN2B (16.0%), KDM5C (14.5%), TP53 (12.9%), PTEN (11.7%), and TERT (9.2%). Eight genes showed prognostic value: CDKN2A, CDKN2B, TP53, PTEN, NF2, PIK3CA, and MTAP were linked to worse prognosis, whereas PBRM1 was associated with better overall survival (OS). Two of the three identified gene clusters had prognostic value: cluster 1 (VHL, SETD2, PBRM1, KDM5C, NFE2L2) correlated with better OS [adjusted hazard ratio (aHR) 0.63, P < 0.001], whereas cluster 3 (CDKN2A, CDKN2B, BAP1, NF2, MTAP) correlated with shorter OS (aHR 1.36, P = 0.023).

CONCLUSION

We identified eight genes and two gene clusters with prognostic significance for mccRCC. Future research will explore the predictive value of gene clusters in various treatments.

UVA-light-induced mutagenesis in the exome of human nucleotide excision repair-deficient cells

Skin cancer is associated with genetic mutations caused by sunlight exposure, primarily through ultraviolet (UV) radiation that damages DNA. While UVA is less energetic, it is the predominant solar UV component reaching the Earth's surface. However, the mechanisms of UVA-induced mutagenesis and its role in skin cancer development remain poorly understood. This study employed whole exome sequencing of clones from human XP-C cells, which lack nucleotide excision repair (NER), to characterize somatic mutations induced by UVA exposure. DNA sequence analysis of UVA-irradiated XP-C cells revealed a marked increase in mutation frequency across nearly all types of base substitutions, with particular enrichment in C > T transitions within the CCN and TCN trinucleotide context-potential sites for pyrimidine dimer formation. The C > T mutation primarily occurred at the 3' base of the 5'TC dimer, and an enrichment of CC > TT tandem mutations. We also identified the SBS7b COSMIC mutational signature within irradiated cells, which has been associated with tumors in sun-exposed skin. C > A transversions, often linked to oxidized guanine, were the second most frequently induced mutation, although a specific context for this base substitution was not identified. Moreover, C > T mutations were significantly increased in unirradiated XP-C compared to NER-proficient cells, which may be caused by unrepaired spontaneous DNA damage. Thus, this study indicates that pyrimidine dimers are the primary lesions contributing to UVA-induced mutagenesis in NER-deficient human cells and demonstrates that UVA generates mutational signatures similar to those of UVB irradiation.

Advances in diagnostic and therapeutic applications of mismatch repair loss in cancer

Mismatch repair (MMR) is a highly conserved, fundamental DNA damage repair pathway that maintains genomic fidelity during cell replication. MMR dysregulation contributes to tumor formation by promoting genomic instability thereby increasing the frequency of potentially oncogenic mutational events. Therefore, MMR dysregulation, in its tumor suppressor role, is largely studied in the context of genomic instability and associated response to immune checkpoint blockade therapies. However, a growing body of literature suggests that the impact of MMR dysregulation on tumor phenotypes is more nuanced than a concerted impact on genomic stability. Rather, loss of individual MMR genes promotes distinct cancer-relevant biological phenotypes, and these phenotypes are further modulated by the tissue of tumor origin. Here, we explore relevant literature and review the prognostic and predictive significance of these non-canonical discoveries.

The Impact of Normal Hepatobiliary Cell Zonation Programs on the Phenotypes and Functions of Primary Liver Tumors

Background

Traditional tumor classifications have relied on cellular origin, pathological morphological features, gene expression profiles, and more recently, the tumor immune microenvironment. While these classifications provide valuable insights, incorporating physiological classifications focusing on liver metabolic functions may lead to new discoveries.

Summary

We proposed to reclassify benign and malignant hepatocellular neoplasms based on their physiological functions such as albumin production, bile acid production, glycolysis, glycogenesis, and adipogenesis. We further demonstrated the homology between signal pathways activated by the differentiation program of the normal hepatobiliary cells and those activated by genetic abnormalities in tumors. Specifically, Wnt/β-catenin, RAS, NOTCH, and TGF-β signaling not only contribute to cell differentiation via activation of liver-enriched transcription factors but also determine the tumor traits. Examining the distinctions between hepatocellular carcinomas (HCCs) that maintain or lose metabolic functions can yield valuable insights into the drivers of biological malignancy and tumor plasticity.

Key Messages

To confirm the homology between the differentiation programs of normal hepatobiliary cells, hepatocellular adenomas (HCA), and HCC we identify liver-specific functions such as catabolism and anabolism within tumors. HCCs and HCAs that have lost these metabolic functions exhibit characteristics such as dedifferentiation, resemblance to biliary cells, or increased glycolysis. Focusing on this underexplored area will likely stimulate active research into new tumor characteristics.

Predicting circRNA-Drug Resistance Associations Based on a Multimodal Graph Representation Learning Framework

Circular RNA (circRNA) is a class of noncoding RNA that is highly conserved and exhibit exceptional stability. Due to its function as a microRNA sponge, circRNA has gained significant attention as an essential biomarker and potential drug target in the pathogenesis of several cancers. Although many circRNAs have been identified to play a role in cancer resistance, traditional methods are time-consuming and expensive. In this context, computational methods offer a promising way to facilitate the discovery process. However, most existing prediction models focus on the association between circRNAs and drug resistance, without considering the corresponding disease-related information in the circRNA-drug resistance association. Incorporating disease-related information into the prediction of circRNA-drug resistance associations could potentially improve the efficiency and speed of discovering and developing circRNA-targeting drugs. We propose a computational framework, named GraphCDD, for predicting the association between circRNA and drug resistance. Our model utilizes data from three sources, namely circRNA, disease, and drug, to construct three similarity networks that represent the features of circRNA, disease, and drug, respectively. We utilize a multimodal graph neural network to acquire efficient representations of circRNAs, diseases, and drugs by integrating various types of information, and establish a predictive model. The experimental results have validated the effectiveness of our model and provided a promising method in predicting potential associations between circRNA and drug resistance.

Personalized, autologous neoantigen-specific T cell therapy in metastatic melanoma: a phase 1 trial

New treatment approaches are warranted for patients with advanced melanoma refractory to immune checkpoint blockade (ICB) or BRAF-targeted therapy. We designed BNT221, a personalized, neoantigen-specific autologous T cell product derived from peripheral blood, and tested this in a 3 + 3 dose-finding study with two dose levels (DLs) in patients with locally advanced or metastatic melanoma, disease progression after ICB, measurable disease (Response Evaluation Criteria in Solid Tumors version 1.1) and, where appropriate, BRAF-targeted therapy. Primary and secondary objectives were evaluation of safety, highest tolerated dose and anti-tumor activity. We report here the non-pre-specified, final results of the completed monotherapy arm consisting of nine patients: three at DL1 (1 × 108-1 × 109 cells) and six at DL2 (2 × 109-1 × 1010 cells). Drug products (DPs) were generated for all enrolled patients. BNT221 was well tolerated across both DLs, with no dose-limiting toxicities of grade 3 or higher attributed to the T cell product observed. Specifically, no cytokine release, immune effector cell-associated neurotoxicity or macrophage activation syndromes were reported. A dose of 5.0 × 108-1.0 × 1010 cells was identified for further study conduct. Six patients showed stable disease as best overall response, and tumor reductions (≤20%) were reported for four of these patients. In exploratory analyses, multiple mutant-specific CD4+ and CD8+ T cell responses were generated in each DP. These were cytotoxic, polyfunctional and expressed T cell receptors with broad functional avidities. Neoantigen-specific clonotypes were detected after treatment in blood and tumor. Our results provide key insights into this neoantigen-specific adoptive T cell therapy and demonstrate proof of concept for this new therapeutic approach. ClinicalTrials.gov registration: NCT04625205 .

A mutational signature and ARID1A mutation associated with outcome in hepatocellular carcinoma

OBJECTIVE

The prognosis of hepatocellular carcinoma (HCC) is poor and there is no stable and reliable molecular biomarker for evaluation. This study attempted to find reliable prognostic markers from tumor mutational profiles.

METHODS

A total of 362 HCC samples with whole-exome sequencing were collected as discovery datasets, and 200 samples with targeted sequencing were used for validation of the relevant results. All HCC samples were obtained from previously published studies. Bayesian non-negative matrix factorization was used to extract mutational signatures, and multivariate Cox regression models were utilized to identify the prognostic role of mutational factors. Gene set enrichment analysis was employed to discover potential signaling pathways associated with specific mutational groups.

RESULTS

In the HCC discovery dataset, a total of four mutational signatures (i.e., signatures 4, 6, 16, and 22) were extracted, of which signature 16 characterized by T>C mutations was observed to be associated with favorable HCC prognosis, and this correlation was also found in the validation dataset. Further analysis showed that patients with ARID1A mutations exhibited inferior survival outcomes in both discovery and validation datasets. Mechanistic exploration revealed that the presence of signature 16 was associated with better immune infiltration and tumor immunogenicity, while patients with ARID1A mutations were away from these favorable immunological features.

CONCLUSION

By integrating somatic mutation data and clinical information of HCC, this study identified that signature 16 and ARID1A mutations were associated with better and worse outcomes respectively, providing a basis for prognosis prediction and clinical treatment strategies of HCC.

The Open Pediatric Cancer Project

Background

In 2019, the Open Pediatric Brain Tumor Atlas (OpenPBTA) was created as a global, collaborative open-science initiative to genomically characterize 1,074 pediatric brain tumors and 22 patient-derived cell lines. Here, we present an extension of the OpenPBTA called the Open Pediatric Cancer (OpenPedCan) Project, a harmonized open-source multi-omic dataset from 6,112 pediatric cancer patients with 7,096 tumor events across more than 100 histologies. Combined with RNA-Seq from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA), OpenPedCan contains nearly 48,000 total biospecimens (24,002 tumor and 23,893 normal specimens).

Findings

We utilized Gabriella Miller Kids First (GMKF) workflows to harmonize WGS, WXS, RNA-seq, and Targeted Sequencing datasets to include somatic SNVs, InDels, CNVs, SVs, RNA expression, fusions, and splice variants. We integrated summarized CPTAC whole cell proteomics and phospho-proteomics data, miRNA-Seq data, and have developed a methylation array harmonization workflow to include m-values, beta-vales, and copy number calls. OpenPedCan contains reproducible, dockerized workflows in GitHub, CAVATICA, and Amazon Web Services (AWS) to deliver harmonized and processed data from over 60 scalable modules which can be leveraged both locally and on AWS. The processed data are released in a versioned manner and accessible through CAVATICA or AWS S3 download (from GitHub), and queryable through PedcBioPortal and the NCI's pediatric Molecular Targets Platform. Notably, we have expanded PBTA molecular subtyping to include methylation information to align with the WHO 2021 Central Nervous System Tumor classifications, allowing us to create research-grade integrated diagnoses for these tumors.

Conclusions

OpenPedCan data and its reproducible analysis module framework are openly available and can be utilized and/or adapted by researchers to accelerate discovery, validation, and clinical translation.

Increased Synthetic Cytotoxicity of Combinatorial Chemoradiation Therapy in Homologous Recombination Deficient Tumors

PURPOSE

Homologous recombination deficient (HRD) tumors are exquisitely sensitive to platinum-based chemotherapy and when combined with radiation therapy (RT), leads to improved overall survival in multiple cancer types. Whether a subset of tumors with distinct molecular characteristics demonstrate increased benefit from cisplatin and RT (c-RT) is unclear. We hypothesized that HRD tumors, whether associated with BRCA mutations or genomic scars of HRD, exhibit exquisite sensitivity to c-RT, and that HRD may be a significant driver of c-RT benefit.

METHODS AND MATERIALS

Sensitivity to c-RT was examined using isogenic and sporadic breast cancer cell lines. HRD was assessed using 4 assays: RT-induced Rad51 foci, a DR-GFP reporter assay, a genomic scar score (large-scale state transitions [LST]), and clonogenic survival assays. Whole-genome sequencing of 4 breast tumors from a phase 2 clinical trial of neoadjuvant c-RT in triple-negative breast cancer was performed and HRD was defined using HRDetect.

RESULTS

BRCA1/2 deficient cell lines displayed functional HRD based on the Rad51 functional assay, with c-RT to RT or cisplatin interaction ratios (IR) of 1.11 and 26.84 for the BRCA1 isogenic pair at 2 μM cisplatin and 6 Gy, respectively. The highest LST lines demonstrated HRD and synthetic cytotoxicity to c-RT with IR at 2 Gy and cisplatin 20 μM of 7.50, and the lowest LST line with IR of 0.65. Of 4 evaluable patients in the phase 2 trial, one achieved a pathologic complete response with corresponding HRD based on multiple genomic scar scores including HRDetect and LST scores, compared with patients without a pathologic complete response.

CONCLUSIONS

HRD breast cancers, whether identified by BRCA1/2 mutation status, functional tests, or mutational signatures, appear to be significantly more sensitive to c-RT compared with isogenic controls or tumors without HRD mutational signatures. HRD tumors may be exquisitely sensitive to c-RT which warrants further clinical investigation to guide a precision oncology approach.

Genomic and Transcriptomic Analysis of Ameloblastoma Reveals Distinct Molecularly Aggressive Phenotypes

Ameloblastoma (AM) is a benign but locally infiltrative epithelial odontogenic neoplasm of the jawbones that may reach grotesque proportions and be highly recurrent if inadequately removed. The BRAFV600E mutation has been demonstrated as a key molecular event in its development; nevertheless, there are many queries about its etiopathogenesis, which are yet to be answered. In this study, we aimed to integrate the results from whole-exome sequencing (WES) and RNA sequencing in AM samples to identify novel candidate genes that may be relevant to its pathogenesis. Thirteen-matched tumors were subjected to WES and RNA-seq, respectively, to detect gene mutations and gene expression profiles, along with the presence of gene fusions. Mutations were validated using Sanger sequencing, whereas transcriptome results were validated using qPCR. The results from both molecular techniques were merged in order to identify novel candidate genes that were biologically validated with immunohistochemistry. BRAFV600E mutation was present in 62% of the analyzed cases, and each AM presented at least 2 or 3 mutations affecting cancer-driver genes. RNA-seq showed different molecular subgroups associated with an aggressive and cancer-related phenotype (epithelial-mesenchymal transition and KRAS gene sets). No gene fusions were detected among the cases. CDH11 and TGM2, novel genes associated with epithelial-mesenchymal transition in AM, were selected and validated in tissues. Both WES and RNA-seq results showed gene alterations related to proliferation, cell differentiation, and metabolic processes. These results show that AM shares many of the hallmarks of cancer secondary to the presence of oncogenic mutations or activation of oncogenic signaling pathways.

Tumor-Infiltrating Lymphocyte Therapy: A New Frontier

In recent years, the successful use of tumor-infiltrating lymphocyte (TIL) therapy to treat melanoma not only culminated in a landmark Food and Drug Administration approval, but has also fueled the emergence of a new, rapidly growing field in TIL cellular immunotherapy surrounding novel enhancements in TIL design, refined manufacturing strategies to enrich for more potent TIL populations, as well as numerous clinical trials now investigating TIL therapy in additional solid tumor types beyond melanoma. This review provides a summary of the latest advances in TIL therapy and what lies ahead for the field. The first section explores several solid cancers that demonstrate the greatest potential for future indications of TIL therapy. The second section provides insight into the promising innovations for designing the next generation of TIL with greater specificity, persistence, safety, and function.

Decoding mutational signatures in breast cancer: Insights from a multi-cohort study

PURPOSE

Diagnosis and treatment decisions of hormonal breast cancers (BC) are now guided by genomic mutations determination, combined into mutational signatures, and provide insight into the patients' genomic landscape. This work aims to compare genomic data and signatures extracted from tissue samples collected in the CICLADES study to existing cohorts. Ultimately, the goal is to prove the accuracy of smaller cohorts and provide new relevant data.

MATERIALS AND METHODS

DNA from patients of the CICLADES cohort was extracted, sequenced, and custom filtering was applied to the resulting files. Genomic data was pulled from 6 BC cohorts available on cBioPortal.com. In total, 2303 samples were analyzed. Mutational signatures were extracted and matched to known signatures of the Catalogue of Somatic Mutations in Cancer (COSMIC). Tumor Mutation Burden (TMB) and hypermutation were estimated and compared between samples.

RESULTS

PIK3CA and TP53 represented the two genes highly mutated across all cohorts. TMB was similar between the CICLADES and CBSM groups, however the MSKCC population showed a significantly higher TMB than both. Nine signatures were extracted, with recurring Single Base Substitutions (SBS) signatures like SBS1, SBS2 and SBS5. The presence of APOBEC-specific signatures was concordant with cohorts presenting APOBEC enrichment. The mean number of mutations was significantly higher in enriched samples for each analyzed cohort.

CONCLUSION

The use of comprehensive genomic profiling provided accurate evaluation of the TMB and extraction of signatures consistent with published literature. The genomic analysis of the tissue samples of the CICLADES cohort brings new and relevant data, comparable to results found in bigger cohorts.

Interpretable identification of cancer genes across biological networks via transformer-powered graph representation learning

Graph representation learning has been leveraged to identify cancer genes from biological networks. However, its applicability is limited by insufficient interpretability and generalizability under integrative network analysis. Here we report the development of an interpretable and generalizable transformer-based model that accurately predicts cancer genes by leveraging graph representation learning and the integration of multi-omics data with the topologies of homogeneous and heterogeneous networks of biological interactions. The model allows for the interpretation of the respective importance of multi-omic and higher-order structural features, achieved state-of-the-art performance in the prediction of cancer genes across biological networks (including networks of interactions between miRNA and proteins, transcription factors and proteins, and transcription factors and miRNA) in pan-cancer and cancer-specific scenarios, and predicted 57 cancer-gene candidates (including three genes that had not been identified by other models) among 4,729 unlabelled genes across 8 pan-cancer datasets. The model's interpretability and generalization may facilitate the understanding of gene-related regulatory mechanisms and the discovery of new cancer genes.

Blood-based biomarkers derived from tumor-informed DNA methylation analysis for lung adenocarcinoma

Objective

To identify robust markers of lung adenocarcinoma (LUAD) using DNA methylation profiles from blood samples informed by tissue lung adenocarcinoma.

Methods

This study analyzed 56 LUAD blood samples from patients attending clinic at Siriraj Hospital, Thailand and 51 samples from healthy participants, using 644 tumor and 59 normal tissue methylome datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases for candidate gene identification. We performed comparative analysis to identify DNA methylation (DNAm) changes present in tumors that are also observable in blood, to be taken forward for validation.

Results

DNAm profiling of lung tumor datasets identified 59,639 differentially methylated positions (DMPs), of which 17,251 exhibited a negative correlation with gene expression. In blood samples, 46,680 DMPs were identified among LUAD patients, which were enriched in pathways associated with the ribosome, spliceosome, cell cycle, ubiquitin mediated proteolysis and nucleocytoplasmic transport. Comparative analysis revealed a two DMP epigenetic signature of matching changes in both tissue and blood. This signature offered high diagnostic performance in distinguishing LUAD from normal lung tissue (AUC: 0.77-0.91) and in blood samples from LUAD patients (AUC:0.92-0.96). Similarly high performance was observed in two independent tissue validation datasets (AUC:0.90-0.92).

Conclusions

Our novel two DMP signatures offer robust performance in both lung tissue and blood for the identification of LUAD.

Advancements in proteogenomics for preclinical targeted cancer therapy research

Advancements in molecular characterization technologies have accelerated targeted cancer therapy research at unprecedented resolution and dimensionality. Integrating comprehensive multi-omic molecular profiling of a tumor, proteogenomics, marks a transformative milestone for preclinical cancer research. In this paper, we initially provided an overview of proteogenomics in cancer research, spanning genomics, transcriptomics, and proteomics. Subsequently, the applications were introduced and examined from different perspectives, including but not limited to genetic alterations, molecular quantifications, single-cell patterns, different post-translational modification levels, subtype signatures, and immune landscape. We also paid attention to the combined multi-omics data analysis and pan-cancer analysis. This paper highlights the crucial role of proteogenomics in preclinical targeted cancer therapy research, including but not limited to elucidating the mechanisms of tumorigenesis, discovering effective therapeutic targets and promising biomarkers, and developing subtype-specific therapies.

Exploring anticancer potential of betanin in DMBA-induced oral squamous cell carcinoma: an in silico and experimental study

In addition to being able to fight cancer, betanin (BTN) has amazing natural antioxidant and peroxy-radical scavenging properties. 7,12-Dimethylbenz[a]anthracene (DMBA) can impair the activities of enzymes accountable for breaking down xenobiotics and can also cause lipid peroxidation. The study's goal was to find out if betanin could protect against these problems. We determined 100% tumor incidence, abnormal tumor volume, inclined tumor burden, and deduced body weight in DMBA-induced hamsters. We observed diminished lipid peroxidation and enzymatic and nonenzymatic antioxidant activities in DMBA-induced hamsters. The histological study showed that the hamster that receives only DMBA undergoes hyperkeratosis, epithelial hyperplasia, dysplasia, and well-differentiated oral squamous cell carcinoma (OSCC). The hamsters received three different dosages of BTN (10, 20, and 40 mg/kg b.w.) via intragastric intubation for 14 weeks, on alternate days of DMBA painting. The levels of antioxidants, xenobiotic enzymes, and lipid peroxidation (LPO) were significantly restored and inhibited tumor development in a dose-dependent manner. The molecular docking study found high levels of binding affinity in Bax (PDB ID: 2K7W), Caspase-3 (PDB ID: 4JJ8), Caspase-9 (PDB ID: 2AR9), PI3K (PDB ID: 5XGI), AKT (PDB ID: 6BUU), p53 (PDB ID: 1YCS), SMAD-2 (PDB ID: 1DEV), SMAD-4 (PDB ID: 1YGS), SMAD-7 (PDB ID: 2DJY), TGFβ-I (PDB ID: 1PY5), and TGFβ-II (PDB ID: 1M9Z). So, therefore, in vivo and in silico studies were providing prominent anticancer activity of betanin against DMBA-induced oral cancer.

KRAS Mutations in Cancer: Understanding Signaling Pathways to Immune Regulation and the Potential of Immunotherapy

The Kirsten rat sarcoma viral oncogene homologue (KRAS) mutation is one of the most prevailing mutations in various tumors and is difficult to cure. Long-term proliferation in carcinogenesis is primarily initiated by oncogenic KRAS-downstream signaling. Recent research suggests that it also activates the autocrine effect and interplays the tumor microenvironment (TME). Here, we discuss the emerging research, including KRAS mutations to immune evasion in TME, which induce immunological modulation that promotes tumor development. This review gives an overview of the existing knowledge of the underlying connection between KRAS mutations and tumor immune modulation. It also addresses the mechanisms to reduce the effect of oncogenes on the immune system and recent advances in clinical trials for immunotherapy in KRAS-mutated cancers.

APOBEC-1 cofactors regulate APOBEC3-induced mutations in hepatitis B virus

APOBEC3 proteins (A3s) play an important role in host innate immunity against viruses and DNA mutations in cancer. A3s-induced mutations in both viral and human DNA genomes vary significantly from non-lethal mutations in viruses to localized hypermutations, such as kataegis in cancer. How A3s are regulated remains largely unknown. Since A3s exist in complexes and belong to the same family as APOBEC-1 (A1), which requires cofactors to be functional, we investigated the role of A1 cofactors and other A3 potentially associated hnRNPs on A3 mutational activity using hepatitis B virus (HBV) cellular replication as a model. We found that A1-associated cofactors and other hnRNPs were involved in A3 mutational activity regulation, and their regulatory effect was dependent on the strength of A3 association with hnRNPs with an order of A3C > 3G>3B and A1 cofactors > other hnRNPs. A1 cofactors had a strong protein interaction with A3 and significantly increased A3 mutational activity by co-expression. Endogenous gene expression knockdown by siRNA had the opposite decrease effect. Disruption of the protein interactions between A3 and hnRNPs through A3G and A3B mutagenesis decreased A3 mutational activity significantly, even to a level of near total loss, indicating that A1 cofactors and hnRNPs are required for A3 mutational activity. HBV genome-wide mutation analyses showed that A1 cofactors significantly increased A3C accessibility to HBV (-)DNA and A3C-induced mutational efficiency to generate kataegis-like hypermutation. These data demonstrate that A1 cofactors and hnRNPs are closely associated with A3s and may play an important regulatory role under physiological conditions.

IMPORTANCE

As human host restriction factors, A3s play an important role against viral infections. A3s are also major mutagenic drivers of cancer. However, why A3-induced mutations vary significantly from non-lethal mutations in virus to localized hypermutations in cancer remains unknown. We found that A1 cofactor and other hnRNPs are not only associated with A3 complexes but also play important regulatory roles in A3-induced mutation activities. A1 cofactors like GRY-RBP significantly increased A3 accessibility and mutational efficiency to its single-strand DNA substrate during HBV reverse transcription to generate hypermutations. Disruption of the A3 protein association with hnRNPs by A3 mutagenesis diminished A3 mutational activity. This finding not only reveals a regulatory mechanism for A3-induced mutation but also indicates that A3-associated cellular factors can be a potential target for regulating A3-induced mutation for cancer therapeutics.

Geographic and age-related variations in mutational processes in colorectal cancer

Colorectal cancer incidence rates vary geographically and have changed over time. Notably, in the past two decades, the incidence of early-onset colorectal cancer, affecting individuals under the age of 50 years, has doubled in many countries. The reasons for this increase are unknown. Here, we investigate whether mutational processes contribute to geographic and age-related differences by examining 981 colorectal cancer genomes from 11 countries. No major differences were found in microsatellite unstable cancers, but variations in mutation burden and signatures were observed in the 802 microsatellite-stable cases. Multiple signatures, most with unknown etiologies, exhibited varying prevalence in Argentina, Brazil, Colombia, Russia, and Thailand, indicating geographically diverse levels of mutagenic exposure. Signatures SBS88 and ID18, caused by the bacteria-produced mutagen colibactin, had higher mutation loads in countries with higher colorectal cancer incidence rates. SBS88 and ID18 were also enriched in early-onset colorectal cancers, being 3.3 times more common in individuals diagnosed before age 40 than in those over 70, and were imprinted early during colorectal cancer development. Colibactin exposure was further linked to APC driver mutations, with ID18 responsible for about 25% of APC driver indels in colibactin-positive cases. This study reveals geographic and age-related variations in colorectal cancer mutational processes, and suggests that early-life mutagenic exposure to colibactin-producing bacteria may contribute to the rising incidence of early-onset colorectal cancer.

The mutational landscape and functional effects of noncoding ultraconserved elements in human cancers

The mutational landscape of phylogenetically ultraconserved elements (UCEs), especially those in noncoding DNAs (ncUCEs), and their functional relevance in cancers remain poorly characterized. Here, we perform a systematic analysis of whole-genome and in-house targeted UCE sequencing datasets from more than 3000 patients with cancer of 13,736 UCEs and demonstrate that ncUCE somatic alterations are common. Using a multiplexed CRISPR knockout screen in colorectal cancer cells, we show that the loss of several altered ncUCEs significantly affects cell proliferation. In-depth functional studies in vitro and in vivo further reveal that specific ncUCEs can be enhancers of tumor suppressors (such as ARID1B) and silencers of oncogenic proteins (such as RPS13). Moreover, several miRNAs located in ncUCEs are recurrently mutated. Mutations in miR-142 locus can affect the Drosha-mediated processing of precursor miRNAs, resulting in the down-regulation of the mature transcript. These results provide systematic evidence that specific ncUCEs play diverse regulatory roles in cancer.

Pharmacogenomics-based subtype decoded implications for risk stratification and immunotherapy in pancreatic adenocarcinoma

BACKGROUND

With fatal malignant peculiarities and poor survival rate, outcomes of pancreatic adenocarcinoma (PAAD) were frustrated by non-response and even resistance to therapy due to heterogeneity across clinical patients. Nevertheless, pharmacogenomics has been developed for individualized-treatment and still maintains obscure in PAAD.

METHODS

A total of 964 samples from 10 independent multi-center cohorts were enrolled in our study. With drug response data from the profiling of relative inhibition simultaneously in mixtures (PRISM) and genomics of drug sensitivity in cancer (GDSC) databases, we established and validated multidimensionally three pharmacogenomics-classified subtypes using non-negative matrix factorization (NMF) and nearest template prediction (NTP) algorithms, separately. The heterogenous biological characteristics and precision medicine strategies among subtypes were further investigated.

RESULTS

Three pharmacogenomics-classified subtypes after stable and reproducible validation, distinguished in six aspects of prognosis, biological peculiarities, immune landscapes, genomic variations, immunotherapy and individualized management strategies. Subtype 2 was close to immunocompetent phenotype and projected to immunotherapy; Subtype 3 held most favorable outcomes and metabolic pathways distinctively, promising to be treated with first-line agents. Subtype 1 with worst prognosis, was anticipated to chromosome instability (CIN) phenotype and resistant to chemotherapeutic agents. In addition, ITGB6 contributed to subtype 1 resistance to 5-fluorouracil, and knockdown of ITGB6 enhanced sensitivity to 5-fluorouracil in in vitro experiments. Ultimately, appropriate clinical stratified treatments were assigned to corresponding subtypes according to pharmacogenomic transcripts. Some limitations were not taken into account, thus needs to be supported by more research.

CONCLUSION

A span-new molecular subtype exploited for PAAD uncovered an insight into precise medication on ground of pharmacogenomics, and highly refined multiple clinical management strategies for specific patients.

A Dirichlet-multinomial mixed model for determining differential abundance of mutational signatures

BACKGROUND

Mutational processes of diverse origin leave their imprints in the genome during tumour evolution. These imprints are called mutational signatures and they have been characterised for point mutations, structural variants and copy number changes. Each signature has an exposure, or abundance, per sample, which indicates how much a process has contributed to the overall genomic change. Mutational processes are not static, and a better understanding of their dynamics is key to characterise tumour evolution and identify cancer cell vulnerabilities that can be exploited during treatment. However, the structure of the data typically collected in this context makes it difficult to test whether signature exposures differ between conditions or time-points when comparing groups of samples. In general, the data consists of multivariate count mutational data (e.g. signature exposures) with two observations per patient, each reflecting a group.

RESULTS

We propose a mixed-effects Dirichlet-multinomial model: within-patient correlations are taken into account with random effects, possible correlations between signatures by making such random effects multivariate, and a group-specific dispersion parameter can deal with particularities of the groups. Moreover, the model is flexible in its fixed-effects structure, so that the two-group comparison can be generalised to several groups, or to a regression setting. We apply our approach to characterise differences of mutational processes between clonal and subclonal mutations across 23 cancer types of the PCAWG cohort. We find ubiquitous differential abundance of clonal and subclonal signatures across cancer types, and higher dispersion of signatures in the subclonal group, indicating higher variability between patients at subclonal level, possibly due to the presence of different clones with distinct active mutational processes.

CONCLUSIONS

Mutational signature analysis is an expanding field and we envision our framework to be used widely to detect global changes in mutational process activity. Our methodology is available in the R package CompSign and offers an ample toolkit for the analysis and visualisation of differential abundance of compositional data such as, but not restricted to, mutational signatures.

Mutation and recombination parameters in zebra finch are similar to those in mammals

Most of our understanding of the fundamental processes of mutation and recombination stems from a handful of disparate model organisms and pedigree studies of mammals, with little known about other vertebrates. To gain a broader comparative perspective, we focused on the zebra finch (Taeniopygia castanotis), which, like other birds, differs from mammals in its karyotype (which includes many micro-chromosomes), in the mechanism by which recombination is directed to the genome, and in aspects of ontogenesis. We collected genome sequences from three generation pedigrees that provide information about 80 meioses, inferring 202 single-point de novo mutations, 1,174 crossovers, and 275 non-crossovers. On that basis, we estimated a sex-averaged mutation rate of 5.0 × 10-9 per base pair per generation, on par with mammals that have a similar generation time (~2-3 years). Also as in mammals, we found a paternal germline mutation bias at later stages of gametogenesis (of 1.7:1) but no discernible difference between sexes in early development. Examining recombination patterns, we found that the sex-averaged crossover rate on macro-chromosomes (1.05 cM/Mb) is again similar to values observed in mammals, as is the spatial distribution of crossovers, with a pronounced enrichment near telomeres. In contrast, non-crossover rates are more uniformly distributed. On micro-chromosomes, sex-averaged crossover rates are substantially higher (4.21 cM/Mb), as expected from crossover homeostasis, and both crossover and non-crossover events are more uniformly distributed. At a finer scale, recombination events overlap CpG islands more often than expected by chance, as expected in the absence of PRDM9. Despite differences in the mechanism by which recombination events are specified and the presence of many micro-chromosomes, estimates of the degree of GC-biased gene conversion (59%), the mean non-crossover conversion tract length (~32 bp), and the non-crossover-to-crossover ratio (5.4:1) are all comparable to those reported in primates and mice. The similarity of mutation and recombination properties in zebra finch to those in mammals suggest that they are conserved by natural selection.

Targeting the PREX2/RAC1/PI3Kβ Signaling Axis Confers Sensitivity to Clinically Relevant Therapeutic Approaches in Melanoma

Metastatic melanoma remains a major clinical challenge. Large-scale genomic sequencing of melanoma has identified bona fide activating mutations in RAC1, which are associated with resistance to BRAF-targeting therapies. Targeting the RAC1-GTPase pathway, including the upstream activator PREX2 and the downstream effector PI3Kβ, could be a potential strategy for overcoming therapeutic resistance, limiting melanoma recurrence, and suppressing metastatic progression. Here, we used genetically engineered mouse models and patient-derived BRAFV600E-driven melanoma cell lines to dissect the role of PREX2 in melanomagenesis and response to therapy. Although PREX2 was dispensable for the initiation and progression of melanoma, its loss conferred sensitivity to clinically relevant therapeutics targeting the MAPK pathway. Importantly, genetic and pharmacologic targeting of PI3Kβ phenocopied PREX2 deficiency, sensitizing model systems to therapy. These data reveal a druggable PREX2/RAC1/PI3Kβ signaling axis in BRAF-mutant melanoma that could be exploited clinically. Significance: Cotargeting the MAPK and the PREX2/RAC1/PI3Kβ pathways has remarkable efficacy and outperforms monotherapy MAPK inhibition in BRAF-mutant melanoma, supporting the potential of this combination therapy for treating metastatic melanoma.

Histologic and Immunologic Factors Associated with Response to Immune Checkpoint Inhibitors in Advanced Sarcoma

PURPOSE

To characterize factors associated with response to immune checkpoint inhibitors (ICI) in advanced sarcoma.

EXPERIMENTAL DESIGN

This is a retrospective study with a cohort of 216 patients with advanced sarcoma treated with ICI between 2016 and 2023 at Stanford Health Care. Overall survival, progression-free survival (PFS), objective response rates (ORR) per RECIST criteria, and reason for ICI discontinuation were analyzed across histologic subtypes, ICI regimens, tumor mutational burden, and PD-L1 expression.

RESULTS

The overall ORR in the cohort was 16.7%. The histologic subtypes with the highest ORR were Kaposi sarcoma (KS, 66.7%), alveolar soft part sarcoma (ASPS, 50%), angiosarcoma (33.3%), myxofibrosarcoma (MFS, 28.6%), and undifferentiated pleomorphic sarcoma (UPS, 27.8%). The subtypes with the lowest ORR were osteosarcoma (0%), synovial sarcoma (0%), and liposarcoma (3.7%). The subtypes with the highest median PFS were KS (median not reached), ASPS (median not reached), MFS (27.4 months), and UPS (11.3 months). The ORR for sarcomas with PD-L1 ≥ 1% was 27.8% (P = 0.02), whereas the ORR for sarcomas with tumor mutational burden ≥10 mutations per megabase of DNA was 28.6% (P = 0.20).

CONCLUSIONS

ORR and PFS were highly variable across sarcoma histologic subtypes. In this large analysis, KS, ASPS, angiosarcoma, MFS, and UPS demonstrated the highest ORR and longest PFS while osteosarcoma, synovial sarcoma, and liposarcoma had the lowest ORR and shortest PFS. PD-L1 expression was also associated with increased ORR. Our findings provide further insight into understanding the sarcoma histologic and immunologic factors that correspond with response to ICI.

Towards the Prediction of Responses to Cancer Immunotherapy: A Multi-Omics Review

Tumor treatment has undergone revolutionary changes with the development of immunotherapy, especially immune checkpoint inhibitors. Because not all patients respond positively to immune therapeutic agents, and severe immune-related adverse events (irAEs) are frequently observed, the development of the biomarkers evaluating the response of a patient is key for the application of immunotherapy in a wider range. Recently, various multi-omics features measured by high-throughput technologies, such as tumor mutation burden (TMB), gene expression profiles, and DNA methylation profiles, have been proved to be sensitive and accurate predictors of the response to immunotherapy. A large number of predictive models based on these features, utilizing traditional machine learning or deep learning frameworks, have also been proposed. In this review, we aim to cover recent advances in predicting tumor immunotherapy response using multi-omics features. These include new measurements, research cohorts, data sources, and predictive models. Key findings emphasize the importance of TMB, neoantigens, MSI, and mutational signatures in predicting ICI responses. The integration of bulk and single-cell RNA sequencing has enhanced our understanding of the tumor immune microenvironment and enabled the identification of predictive biomarkers like PD-L1 and IFN-γ signatures. Public datasets and machine learning models have also improved predictive tools. However, challenges remain, such as the need for large and diverse clinical datasets, standardization of multi-omics data, and model interpretability. Future research will require collaboration among researchers, clinicians, and data scientists to address these issues and enhance cancer immunotherapy precision.

Multi-omics analyses reveal biological and clinical insights in recurrent stage I non-small cell lung cancer

Post-operative recurrence rates of stage I non-small cell lung cancer (NSCLC) range from 20% to 40%. Nonetheless, the molecular mechanisms underlying recurrence hitherto remain largely elusive. Here, we generate genomic, epigenomic and transcriptomic profiles of paired tumors and adjacent tissues from 122 stage I NSCLC patients, among which 57 patients develop recurrence after surgery during follow-up. Integrated analyses illustrate that the presence of predominantly solid or micropapillary histological subtypes, increased genomic instability, and APOBEC-related signature are associated with recurrence. Furthermore, TP53 missense mutation in DNA-binding domain could contribute to shorter time to recurrence. DNA hypomethylation is pronounced in recurrent NSCLC, and PRAME is the significantly hypomethylated and overexpressed gene in recurrent lung adenocarcinoma (LUAD). Mechanistically, hypomethylation at TEAD1 binding site facilitates the transcriptional activation of PRAME. Inhibition of PRAME restrains the tumor metastasis via downregulation of epithelial-mesenchymal transition-related genes. We also identify that enrichment of AT2 cells with higher copy number variation burden, exhausted CD8 + T cells and Macro_SPP1, along with the reduced interaction between AT2 and immune cells, is essential for the formation of ecosystem in recurrent LUAD. Finally, multi-omics clustering could stratify the NSCLC patients into 4 subclusters with varying recurrence risk and subcluster-specific therapeutic vulnerabilities. Collectively, this study constitutes a promising resource enabling insights into the biological mechanisms and clinical management for post-operative recurrence of stage I NSCLC.

Tumor-initiating and metastasis-initiating cells of clear-cell renal cell carcinoma

Clear-cell renal cell carcinoma (ccRCC) is the most common subtype of kidney malignancy. ccRCC is considered a major health concern worldwide because its numbers of incidences and deaths continue to rise and are predicted to continue rising in the foreseeable future. Therefore new strategy for early diagnosis and therapeutics for this disease is urgently needed. The discovery of cancer stem cells (CSCs) offers hope for early cancer detection and treatment. However, there has been no definitive identification of these cancer progenitors for ccRCC. A majority of ccRCC is characterized by the loss of the von Hippel-Lindau (VHL) tumor suppressor gene function. Recent advances in genome analyses of ccRCC indicate that in ccRCC, tumor-initiating cells (TICs) and metastasis-initiating cells (MICs) are two distinct groups of progenitors. MICs result from various genetic changes during subclonal evolution, while TICs reside in the stem of the ccRCC phylogenetic tree of clonal development. TICs likely originate from kidney tubule progenitor cells bearing VHL gene inactivation, including chromatin 3p loss. Recent studies also point to the importance of microenvironment reconstituted by the VHL-deficient kidney tubule cells in promoting ccRCC initiation and progression. These understandings should help define the progenitors of ccRCC and facilitate early detection and treatment of this disease.

Treatment for hepatocellular carcinoma after immunotherapy

Immunotherapy has revolutionized the treatment landscape for advanced HCC, resulting in prolonged response and improved survival. With these results, a pressing question arises: what is the optimal treatment following first-line immunotherapy? Despite the benefits of immunotherapy, most patients will experience disease progression within six months and will require subsequent therapies. International guidelines recommend second-line multi-kinase inhibitors following progression on immunotherapy; however, this recommendation is primarily based on expert consensus rather than high-quality evidence. Nevertheless, real-world data indicate that these agents demonstrate similar efficacy and safety when used as first-line treatments. Conversely, it remains unclear whether continuing immunotherapy after progression is beneficial. In some cases, adding anti-CTLA-4 as salvage therapy has shown effectiveness. Molecular-directed therapies have also been tested, showing some initial promise, but further data is needed to confirm the benefits of this approach. Emerging evidence suggests that patients experiencing oligoprogression may benefit from local or locoregional therapies while continuing immunotherapy. In this review, we will discuss treatment strategies following progression after first-line immunotherapy.

Ionizing Radiation May Induce Tumors Partly Through the Alteration or Regulation of Mismatch Repair Genes

Ionizing radiation is mutagenic and carcinogenic, and it is reported to induce primary and secondary tumors with intestinal tumors being one of the most commonly observed. However, the pathological and molecular mechanism(s) underlying the radiation-associated tumorigenesis remain unclear. A link between radiation and somatic tumorigenesis partly through genetic, epigenetic alteration and/or regulation of mismatch repair (MMR) genes has been hypothesized for the first time within this review. Clinical observations and experimental findings provide significant support for this association including MMR mutations as well as altered MMR RNA and protein expressions that occurred post-exposure, although existing evidence in published literature is sparse in this niche area. Some speculative mechanisms are suggested with this review to inform future research. Further studies are needed to understand the roles of the MMR system in response to radiation and to test this possible connection which could potentially provide useful and urgently needed information for clinical guidance.

Spontaneous Necrosis of a High-Risk Bladder Tumor Under Immunotherapy for Concurrent Malignant Melanoma: Role of BRAF Mutations and PD-L1 Expression

Background: Bladder cancer (BC) is a heterogeneous malignancy, and predicting response to immune checkpoint inhibitors (ICIs) remains a challenge. Herein, we investigate a high-risk bladder tumor, which developed during anti-BRAF/MEK therapy for a concurrent advanced BRAF-V600E-positive malignant melanoma (MM) and subsequently underwent complete spontaneous necrosis following Nivolumab immunotherapy, only to recur thereafter while still under the same treatment. This unique scenario provided an opportunity to investigate the roles of BRAF gene mutations in BC pathogenesis, respectively, of PD-L1 expression in immunotherapy response prediction. Methods: We retrospectively analyzed BC specimens obtained via transurethral resection at two critical time-points: prior to the complete spontaneous necrosis under Nivolumab (prenecrosis) and after tumor recurrence postnecrosis (postnecrosis). The BRAF gene mutation status was evaluated using quantitative polymerase chain reaction (qPCR). PD-L1 expression was assessed by immunohistochemistry (IHC), quantified using the combined positive score (CPS), and a cutoff of ≥10 for positivity. Results: Neither pre- nor postnecrosis BC samples harbored BRAF gene mutations. Prenecrosis PD-L1 expression (CPS = 5) indicated a minimal likelihood of response to immunotherapy. However, complete spontaneous necrosis occurred under Nivolumab, followed by recurrence with further reduced PD-L1 expression (CPS = 1). Conclusions: The complete BC regression challenges the conventional role of PD-L1 as a sole predictive biomarker for immunotherapy. This study also highlights the potential role of BRAF/MEK inhibitors in BC oncogenesis and underscores the need for alternative biomarkers, such as tumor mutation burden (TMB) and circulating tumor DNA (ctDNA), to guide treatment selection in BC better.

MONet: cancer driver gene identification algorithm based on integrated analysis of multi-omics data and network models

Cancer progression is orchestrated by the accrual of mutations in driver genes, which endow malignant cells with a selective proliferative advantage. Identifying cancer driver genes is crucial for elucidating the molecular mechanisms of cancer, advancing targeted therapies, and uncovering novel biomarkers. Based on integrated analysis of Multi-Omics data and Network models, we present MONet, a novel cancer driver gene identification algorithm. Our method utilizes two graph neural network algorithms on protein-protein interaction (PPI) networks to extract feature vector representations for each gene. These feature vectors are subsequently concatenated and fed into a multi-layer perceptron model (MLP) to perform semi-supervised identification of cancer driver genes. For each mutated gene, MONet assigns the probability of being potential driver, with genes identified in at least two PPI networks selected as candidate driver genes. When applied to pan-cancer datasets, MONet demonstrated robustness across various PPI networks, outperforming baseline models in terms of both the area under the receiver operating characteristic curve and the area under the precision-recall curve. Notably, MONet identified 37 novel driver genes that were missed by other methods, including 29 genes such as APOBEC2, GDNF, and PRELP, which are corroborated by existing literature, underscoring their critical roles in cancer development and progression. Through the MONet framework, we successfully identified known and novel candidate cancer driver genes, providing biologically meaningful insights into cancer mechanisms.

Mapping naturally presented T cell antigens in medulloblastoma based on integrative multi-omics

Medulloblastoma is the most frequent malignant primary brain tumor in children. Despite recent advances in integrated genomics, the prognosis in children with high-risk medulloblastoma remains devastating, and new tumor-specific therapeutic approaches are needed. Here, we present an atlas of naturally presented T cell antigens in medulloblastoma. We map the human leukocyte antigen (HLA)-presented peptidomes of 28 tumors and perform comparative immunopeptidome profiling against an in-house benign database. Medulloblastoma is shown to be a rich source of tumor-associated antigens, naturally presented on HLA class I and II molecules. Remarkably, most tumor-associated peptides and proteins are subgroup-specific, whereas shared presentation among all subgroups of medulloblastoma (WNT, SHH, Group 3 and Group 4) is rare. Functional testing of top-ranking novel candidate antigens demonstrates the induction of peptide-specific T cell responses, supporting their potential for T cell immunotherapy. This study is an in-depth mapping of naturally presented T cell antigens in medulloblastoma. Integration of immunopeptidomics, transcriptomics, and epigenetic data leads to the identification of a large set of actionable targets that can be further used for the translation into the clinical setting by facilitating the informed design of immunotherapeutic approaches to children with medulloblastoma.

An Expanding Universe of Mutational Signatures and Its Rapid Evolution in Single-Stranded RNA Viruses

The study of mutational processes in somatic genomes has gained recent momentum, uncovering a wide array of endogenous and exogenous factors associated with somatic changes. However, the overall landscape of mutational processes in germline mutations across the tree of life and associated evolutionary driving forces are rather unclear. In this study, we analyzed mutational processes in single-stranded RNA (ssRNA) viruses which are known to jump between different hosts with divergent exogenous environments. We found that mutational spectra in different ssRNA viruses differ significantly and are mainly associated with their genetic divergence. Surprisingly, host environments contribute much less significantly to the mutational spectrum, challenging the prevailing view that the exogenous cellular environment is a major determinant of the mutational spectrum in viruses. To dissect the evolutionary forces shaping viral spectra, we selected two important scenarios, namely the inter-host evolution between different viral strains as well as the intra-host evolution. In both scenarios, we found mutational spectra change significantly through space and time, strongly correlating with levels of natural selection. Combining the mutations across all ssRNA viruses, we identified a suite of mutational signatures with varying degrees of similarity to somatic signatures in humans, indicating universal and divergent mutational processes across the tree of life. Taken together, we unraveled an unprecedented dynamic landscape of mutational processes in ssRNA viruses, pinpointing important evolutionary forces shaping fast evolution of mutational spectra in different species.

Shining a light on cell biology of the nucleus with single-cell sequencing

From the preservation of genomic integrity to the regulation of RNA translation, nearly all cellular processes are regulated in a cell context-dependent manner. To fully understand the context-specific function of involved nuclear processes, a vast number of single-cell sequencing technologies were developed over the last decade. This instrumental work demonstrated the heterogeneity between cell types and individual cells, bringing about new understanding of nuclear mechanisms and their crosstalk to cell states. In this review, we will cover new technological advances and their exciting applications as well as future opportunities to discover new nuclear processes and the crosstalk between them.

The p12 Subunit Choreographs the Regulation and Functions of Two Forms of DNA Polymerase δ in Mammalian Cells

There are two forms of DNA polymerase δ in human cells, Pol δ4 and Pol δ3, which differ based on their possession of the p12 subunit. The degradation of p12 has emerged as an important regulatory mechanism that controls the generation of Pol δ3. The underlying importance of this system lies in the altered enzymatic properties of the two forms of Pol δ engendered by the influence of p12. We briefly review how the balance of these two forms is regulated through the degradation of p12. We focus on the roles of Pol δ4, whose cellular functions are less well known. This is significant because recent studies show that this is the form engaged in the homology-dependent repair of double-strand breaks. We consider new horizons for future research into this system and their potential involvement in tumorigenesis.

Tumor mutational burden: why is it still a controversial agnostic immunotherapy biomarker?

For the past few years, researchers and oncologists have been pushing to find biomarkers that would help predict which treatment option would best work on a patient. Tumor Mutational Burden (TMB) is one of the latest biomarkers that is being studied and considered as a promising agnostic immunotherapy biomarker. However, it still shows controversial results in studies due to the difficulty in finding solid comparable results. This is a consequence of different cutoff definitions among many cancer types, age ranges, and the use of different sequencing assays, in addition to its association with other biomarkers such as PD-L1. Finally, the use of composite biomarkers to assess the genetic signature of a tumor might be the way forward to seriously use TMB as an agnostic biomarker.

Gallbladder cholangiocyte organoids

Organoids are miniature three-dimensional (3D) organ-like structures developed from primary cells that closely mimic the key histological, functional, and molecular characteristics of their parent organs. These structures self-organize through cell-cell and cell-matrix interaction in culture. In the last decade, organoids and allied 3D culture technologies have catalyzed studies involving developmental biology, disease biology, high-throughput drug screening, personalized medicine, biomarker discovery, tissue engineering, and regenerative medicine. Many organoid systems have been generated from the gastrointestinal system, for example, intestine, stomach, liver, pancreas, or colon. Gallbladder cancer (GBC) is the most common and highly aggressive form of biliary tract cancer. GBC is rare in the west but has a high incidence in South America and India. Prolonged chronic inflammation is implicated in the pathogenesis of GBC but the driving molecular pathways leading to neoplasia are not well understood. Gallbladder cholangiocyte organoids (GCO) will facilitate the understanding of the evolution of the disease and novel therapeutic strategies. In this review, we have discussed alternative methodologies and culture conditions developed to generate GCO models, applications that these models have been subjected to and the current limitations for the use of GCOs in addressing the challenges in GBC research.

Disruption of deoxyribonucleotide triphosphate biosynthesis leads to RAS proto-oncogene activation and perturbation of mitochondrial metabolism

Perturbation of the deoxyribonucleotide triphosphate (dNTP) pool is recognized for contributing to the mutagenic processes involved in oncogenesis. The RAS gene family encodes well-characterized oncoproteins whose structure and function are among the most frequently altered in several cancers. In this work, we show that fluctuation of the dNTP pool induces CG → TA mutations across the whole genome, including RAS gene at codons for glycine 12 and 13, known hotspots in cancers. Cell culture addition of the ribonucleotide reductase inhibitor thymidine increases the mutation frequency in nuclear DNA and leads to disruption of mitochondrial metabolism. Interestingly, this effect is counteracted by the addition of deoxycytidine. Finally, screening for the loss of hydrogen bonds detecting CG → TA transition in RAS gene of 135 patients with colorectal cancer confirmed the clinical relevance of this process. All together, these data demonstrate that fluctuation of intracellular dNTP pool alters the nuclear DNA and mitochondrial metabolism.

Applications and emerging challenges of single-cell RNA sequencing technology in tumor drug discovery

Current therapeutic drugs are inadequate for curing tumors, highlighting the need for novel tumor drugs. The advancement of single-cell RNA sequencing (scRNA-seq) technology offers new opportunities for tumor drug discovery. This technology allows us to explore tumor heterogeneity and developmental mechanisms at the single-cell level. In this review, we outline the application of scRNA-seq in tumor drug discovery stages, including elucidating tumor mechanisms, identifying targets, screening drugs, and understanding drug action and resistance. We also discuss the challenges and future prospects of using scRNA-seq in drug development, providing a scientific foundation for advancing tumor therapies.

Technological advances in clinical individualized medication for cancer therapy: from genes to whole organism

Efforts have been made to leverage technology to accurately identify tumor characteristics and predict how each cancer patient may respond to medications. This involves collecting data from various sources such as genomic data, histological information, functional drug profiling, and drug metabolism using techniques like polymerase chain reaction, sanger sequencing, next-generation sequencing, fluorescence in situ hybridization, immunohistochemistry staining, patient-derived tumor xenograft models, patient-derived organoid models, and therapeutic drug monitoring. The utilization of diverse detection technologies in clinical practice has made "individualized treatment" possible, but the desired level of accuracy has not been fully attained yet. Here, we briefly summarize the conventional and state-of-the-art technologies contributing to individualized medication in clinical settings, aiming to explore therapy options enhancing clinical outcomes.

Pathogenesis and inflammaging in myelodysplastic syndrome

Myelodysplastic syndromes (MDS) are a genetically complex and phenotypically diverse set of clonal hematologic neoplasms that occur with increasing frequency with age. MDS has long been associated with systemic inflammatory conditions and disordered inflammatory signaling is implicated in MDS pathogenesis. A rise in sterile inflammation occurs with ageing and the term "inflammaging" has been coined by to describe this phenomenon. This distinct form of sterile inflammation has an unknown role in in the pathogenesis of myeloid malignancies despite shared correlations with age and ageing-related diseases. More recent is a discovery that many cases of MDS arise from clonal hematopoiesis of indeterminate potential (CHIP), an age associated, asymptomatic pre-disease state. The interrelationship between ageing, inflammation and clonal CHIP is complex and likely bidirectional with causality between inflammaging and CHIP potentially instrumental to understanding MDS pathogenesis. Here we review the concept of inflammaging and MDS pathogenesis and explore their causal relationship by introducing a novel framing mechanism of "pre-clonal inflammaging" and "clonal inflammaging". We aim to harmonize research on ageing, inflammation and MDS pathogenesis by contextualizing the current understanding of inflammaging and the ageing hematopoietic system with what is known about the etiology of MDS via its progression from CHIP.

Immune checkpoint inhibitors for glioblastoma: emerging science, clinical advances, and future directions

Glioblastoma (GBM), the most common and aggressive primary central nervous system (CNS) tumor in adults, continues to have a dismal prognosis. Across hundreds of clinical trials, few novel approaches have translated to clinical practice while survival has improved by only a few months over the past three decades. Randomized controlled trials of immune checkpoint inhibitors (ICIs), which have seen impressive success for advanced or metastatic extracranial solid tumors, have so far failed to demonstrate a clinical benefit for patients with GBM. This has been secondary to GBM heterogeneity, the unique immunosuppressive CNS microenvironment, immune-evasive strategies by cancer cells, and the rapid evolution of tumor on therapy. This review aims to summarize findings from major clinical trials of ICIs for GBM, review historic failures, and describe currently promising avenues of investigation. We explore the biological mechanisms driving ICI responses, focusing on the role of the tumor microenvironment, immune evasion, and molecular biomarkers. Beyond conventional monotherapy approaches targeting PD-1, PD-L1, CTLA-4, we describe emerging approaches for GBM, such as dual-agent ICIs, and combination of ICIs with oncolytic virotherapy, antigenic peptide vaccines, chimeric antigenic receptor (CAR) T-cell therapy, along with nanoparticle-based delivery systems to enhance ICI efficacy. We highlight potential strategies for improving patient selection and treatment personalization, along with real-time, longitudinal monitoring of therapeutic responses through advanced imaging and liquid biopsy techniques. Integrated radiomics, tissue, and plasma-based analyses, may potentially uncover immunotherapeutic response signatures, enabling early, adaptive therapeutic adjustments. By specifically targeting current therapeutic challenges, outcomes for GBM patients may potentially be improved.

HPV-driven oncogenesis-much more than the E6 and E7 oncoproteins

High-risk human papillomaviruses are well-established drivers of several cancer types including cervical, head and neck, penile as well as anal cancers. While the E6 and E7 viral oncoproteins have proven to be critical for malignant transformation, evidence is also beginning to emerge suggesting that both host pathways and additional viral genes may also be pivotal for malignant transformation. Here, we focus on the role of host APOBEC genes, which have an important role in molecular editing including in the response to the viral DNA and their role in HPV-driven carcinogenesis. Further, we also discuss data developed suggesting the existence of HPV-derived miRNAs in HPV + tumors and their potential role in regulating the host transcriptome. Collectively, while recent advances in these two areas have added complexity to the working model of papillomavirus-induced oncogenesis, these discoveries have also shed a light onto new areas of research that will be required to fully understand the process.

Unprecedented female mutation bias in the aye-aye, a highly unusual lemur from Madagascar

Every mammal studied to date has been found to have a male mutation bias: male parents transmit more de novo mutations to offspring than female parents, contributing increasingly more mutations with age. Although male-biased mutation has been studied for more than 75 years, its causes are still debated. One obstacle to understanding this pattern is its near universality-without variation in mutation bias, it is difficult to find an underlying cause. Here, we present new data on multiple pedigrees from two primate species: aye-ayes (Daubentonia madagascariensis), a member of the strepsirrhine primates, and olive baboons (Papio anubis). In stark contrast to the pattern found across mammals, we find a much larger effect of maternal age than paternal age on mutation rates in the aye-aye. In addition, older aye-aye mothers transmit substantially more mutations than older fathers. We carry out both computational and experimental validation of our results, contrasting them with results from baboons and other primates using the same methodologies. Further, we analyze a set of DNA repair and replication genes to identify candidate mutations that may be responsible for the change in mutation bias observed in aye-ayes. Our results demonstrate that mutation bias is not an immutable trait, but rather one that can evolve between closely related species. Further work on aye-ayes (and possibly other lemuriform primates) should help to explain the molecular basis for sex-biased mutation.

Molecular biomarkers of progression in non-muscle-invasive bladder cancer - beyond conventional risk stratification

The global incidence of bladder cancer is more than half a million diagnoses each year. Bladder cancer can be categorized into non-muscle-invasive bladder cancer (NMIBC), which accounts for ~75% of diagnoses, and muscle-invasive bladder cancer (MIBC). Up to 45% of patients with NMIBC develop disease progression to MIBC, which is associated with a poor outcome, highlighting a clinical need to identify these patients. Current risk stratification has a prognostic value, but relies solely on clinicopathological parameters that might not fully capture the complexity of disease progression. Molecular research has led to identification of multiple crucial players involved in NMIBC progression. Identified biomarkers of progression are related to cell cycle, MAPK pathways, apoptosis, tumour microenvironment, chromatin stability and DNA-damage response. However, none of these biomarkers has been prospectively validated. Reported gene signatures of progression do not improve NMIBC risk stratification. Molecular subtypes of NMIBC have improved our understanding of NMIBC progression, but these subtypes are currently unsuitable for clinical implementation owing to a lack of prospective validation, limited predictive value as a result of intratumour subtype heterogeneity, technical challenges, costs and turnaround time. Future steps include the development of consensus molecular NMIBC subtypes that might improve conventional clinicopathological risk stratification. Prospective implementation studies of biomarkers and the design of biomarker-guided clinical trials are required for the integration of molecular biomarkers into clinical practice.

Recent advances in development and delivery of non-viral nucleic acid therapeutics for brain tumor therapy

High grade gliomas (HGG) are a group of CNS tumors refractory to currently existing therapies, which routinely leads to early recurrence and a dismal prognosis. Recent advancements in nucleic acid-based therapy using a wide variety of different molecular targets and non-viral nanocarrier systems suggest that this approach holds significant potential to meet the urgent demand for improved therapeutic options for the treatment of these tumors. This review provides a comprehensive and up-to-date overview on the current landscape and progress of preclinical and clinical developments in this rapidly evolving and exciting field of research, including optimized nanocarrier delivery systems, promising therapeutic targets and tailor-made therapeutic strategies for individualized HGG patient treatment.