Pan-cancer analysis of whole genomes

Characterization of Exhausted T Cell Signatures in Pan-Cancer Settings

T cells play diverse roles in cancer immunology, acting as tumor suppressors, cytotoxic effectors, enhancers of cytotoxic T lymphocyte responses and immune suppressors; providing memory and surveillance; modulating the tumor microenvironment (TME); or activating innate immune cells. However, cancer cells can disrupt T cell function, leading to T cell exhaustion and a weakened immune response against the tumor. The expression of exhausted T cell (Tex) markers plays a pivotal role in shaping the immune landscape of multiple cancers. Our aim was to systematically investigate the role of known T cell exhaustion (Tex) markers across multiple cancers while exploring their molecular interactions, mutation profiles, and potential implications for immunotherapy. The mRNA expression profile of six Tex markers, LAG-3, PDCD1, TIGIT, HAVCR2, CXCL13, and LAYN was investigated in pan-cancer. Utilizing data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), The Cancer Proteome Atlas (TCPA), and other repositories, we characterized the differential expression of the Tex markers, their association with the patients' survival outcome, and their mutation profile in multiple cancers. Additionally, we analyzed the effects on cancer-related pathways and immune infiltration within the TME, offering valuable insights into mechanisms of cancer immune evasion and progression. Finally, the correlation between their expression and sensitivity to multiple anti-cancer drugs was investigated extensively. Differential expression of all six markers was significantly associated with KIRC and poor prognosis in several cancers. They also played a potential activating role in apoptosis, EMT, and hormone ER pathways, as well as a potential inhibitory role in the DNA damage response and RTK oncogenic pathways. Infiltration of different immune cells was also found to be associated with the expression of the Tex-related genes in most cancer types. These findings underline that the reviving of exhausted T cells can be used to enhance the efficacy of immunotherapy in cancer patients.

RHOA Loss of Function Impairs the IFNγ Response and Promotes CD19 Antigen Escape to Drive CAR-T Resistance in Diffuse Large B-cell Lymphoma

CD19-directed chimeric antigen receptor (CAR)-T cells are breakthrough therapies for aggressive B-cell lymphomas, but less than half of patients achieve durable responses. We previously showed through whole-genome sequencing of tumors from CAR-T-treated patients that deletions of RHOA (3p21.31) are enriched in cases progressing after treatment. RHOA 's roles in resistance and pathogenesis are poorly defined, despite loss-of-function alterations that occur in ~20% of newly diagnosed diffuse large B-cell lymphoma (DLBCL) cases. To evaluate mechanisms of CAR-T resistance, we created RHOA-deficient DLBCL systems and confirmed cell-intrinsic loss of response to CAR-19 in vitro and in vivo. RHOA loss promotes AKT activation that impairs cell-intrinsic responses to interferon gamma (IFNγ). Moreover, expression of the CAR target CD19 is consistently down-regulated accompanied by a drive toward plasmablast differentiation. RHOA deficient tumors demonstrate greatly increased sensitivity to AKT-pathway inhibitors, which reverse impaired IFNγ responses. Lymphoma microenvironments in vivo in immunocompetent mice reveal that RHOA loss promotes decreased infiltration by cytotoxic T cells and enrichment of M2-polarized macrophages, known markers of CAR-T resistance in lymphoma clinical cases. Overall, we characterize RHOA deficiency as an AKT-mediated CAR-T resistance driver and implicate avoidance of T-cell mediated killing as a likely reason for RHOA's frequent loss in DLBCL pathogenesis.

Structural variant and nucleosome occupancy dynamics postchemotherapy in a HER2+ breast cancer organoid model

The most common chemotherapeutics induce DNA damage to eradicate cancer cells, yet defective DNA repair can propagate mutations, instigating therapy resistance and secondary malignancies. Structural variants (SVs), arising from copy-number-imbalanced and -balanced DNA rearrangements, are a major driver of tumor evolution, yet understudied posttherapy. Here, we adapted single-cell template-strand sequencing (Strand-seq) to a HER2+ breast cancer model to investigate the formation of doxorubicin-induced de novo SVs. We coupled this approach with nucleosome occupancy (NO) measurements obtained from the same single cell to enable simultaneous SV detection and cell-type classification. Using organoids from TetO-CMYC/TetO-Neu/MMTV-rtTA mice modeling HER2+ breast cancer, we generated 459 Strand-seq libraries spanning various tumorigenesis stages, identifying a 7.4-fold increase in large chromosomal alterations post-doxorubicin. Complex DNA rearrangements, deletions, and duplications were prevalent across basal, luminal progenitor (LP), and mature luminal (ML) cells, indicating uniform susceptibility of these cell types to SV formation. Doxorubicin further elevated sister chromatid exchanges (SCEs), indicative of genomic stress persisting posttreatment. Altered nucleosome occupancy levels on distinct cancer-related genes further underscore the broad genomic impact of doxorubicin. The organoid-based system for single-cell multiomics established in this study paves the way for unraveling the most important therapy-associated SV mutational signatures, enabling systematic studies of the effect of therapy on cancer evolution.

Role of AI in empowering and redefining the oncology care landscape: perspective from a developing nation

Early diagnosis and accurate prognosis play a pivotal role in the clinical management of cancer and in preventing cancer-related mortalities. The burgeoning population of Asia in general and South Asian countries like India in particular pose significant challenges to the healthcare system. Regrettably, the demand for healthcare services in India far exceeds the available resources, resulting in overcrowded hospitals, prolonged wait times, and inadequate facilities. The scarcity of trained manpower in rural settings, lack of awareness and low penetrance of screening programs further compounded the problem. Artificial Intelligence (AI), driven by advancements in machine learning, deep learning, and natural language processing, can profoundly transform the underlying shortcomings in the healthcare industry, more for populous nations like India. With about 1.4 million cancer cases reported annually and 0.9 million deaths, India has a significant cancer burden that surpassed several nations. Further, India's diverse and large ethnic population is a data goldmine for healthcare research. Under these circumstances, AI-assisted technology, coupled with digital health solutions, could support effective oncology care and reduce the economic burden of GDP loss in terms of years of potential productive life lost (YPPLL) due to India's stupendous cancer burden. This review explores different aspects of cancer management, such as prevention, diagnosis, precision treatment, prognosis, and drug discovery, where AI has demonstrated promising clinical results. By harnessing the capabilities of AI in oncology research, healthcare professionals can enhance their ability to diagnose cancers at earlier stages, leading to more effective treatments and improved patient outcomes. With continued research and development, AI and digital health can play a transformative role in mitigating the challenges posed by the growing population and advancing the fight against cancer in India. Moreover, AI-driven technologies can assist in tailoring personalized treatment plans, optimizing therapeutic strategies, and supporting oncologists in making well-informed decisions. However, it is essential to ensure responsible implementation and address potential ethical and privacy concerns associated with using AI in healthcare.

Decoding the functional impact of the cancer genome through protein-protein interactions

Acquisition of genomic mutations enables cancer cells to gain fitness advantages under selective pressure and, ultimately, leads to oncogenic transformation. Interestingly, driver mutations, even within the same gene, can yield distinct phenotypes and clinical outcomes, necessitating a mutation-focused approach. Conversely, cellular functions are governed by molecular machines and signalling networks that are mostly controlled by protein-protein interactions (PPIs). The functional impact of individual genomic alterations could be transmitted through regulated nodes and hubs of PPIs. Oncogenic mutations may lead to modified residues of proteins, enabling interactions with other proteins that the wild-type protein does not typically interact with, or preventing interactions with proteins that the wild-type protein usually interacts with. This can result in the rewiring of molecular signalling cascades and the acquisition of an oncogenic phenotype. Here, we review the altered PPIs driven by oncogenic mutations, discuss technologies for monitoring PPIs and provide a functional analysis of mutation-directed PPIs. These driver mutation-enabled PPIs and mutation-perturbed PPIs present a new paradigm for the development of tumour-specific therapeutics. The intersection of cancer variants and altered PPI interfaces represents a new frontier for understanding oncogenic rewiring and developing tumour-selective therapeutic strategies.

The complex interplay between aging and cancer

Cancer is an age-related disease, but the interplay between cancer and aging is complex and their shared molecular drivers are deeply intertwined. This Review provides an overview of how different biological pathways affect cancer and aging, leveraging evidence mainly derived from animal studies. We discuss how genome maintenance and accumulation of DNA mutations affect tumorigenesis and tissue homeostasis during aging. We describe how age-related telomere dysfunction and cellular senescence intricately modulate tumor development through mechanisms involving genomic instability and inflammation. We examine how an aged immune system and chronic inflammation shape tumor immunosurveillance, fueling DNA damage and cellular senescence. Finally, as animal models are important to untangling the relative contributions of these aging-modulated pathways to cancer progression and to test interventions, we discuss some of the limitations of physiological and accelerated aging models, aiming to improve experimental designs and enhance translation.

Pathological diagnosis of central nervous system tumours in adults: what's new?

In the course of the last decade, the pathological diagnosis of many tumours of the central nervous system (CNS) has transitioned from a purely histological to a combined histological and molecular approach, resulting in a more precise 'histomolecular diagnosis'. Unfortunately, translation of this refinement in CNS tumour diagnostics into more effective treatment strategies is lagging behind. There is hope though that incorporating the assessment of predictive markers in the pathological evaluation of CNS tumours will help to improve this situation. The present review discusses some novel aspects with regard to the pathological diagnosis of the most common CNS tumours in adults. After a brief update on recognition of clinically meaningful subgroups in adult-type diffuse gliomas and the value of assessing predictive markers in these tumours, more detailed information is provided on predictive markers of (potential) relevance for immunotherapy especially for glioblastomas, IDH-wildtype. Furthermore, recommendations for improved grading of meningiomas by using molecular markers are briefly summarised, and an overview is given on (predictive) markers of interest in metastatic CNS tumours. In the last part of this review, some 'emerging new CNS tumour types' that may occur especially in adults are presented in a table. Hopefully, this review provides useful information on 'what's new' for practising pathologists diagnosing CNS tumours in adults.

iModEst: disentangling -omic impacts on gene expression variation across genes and tissues

Many regulatory factors impact the expression of individual genes including, but not limited, to microRNA, long non-coding RNA (lncRNA), transcription factors (TFs), cis-methylation, copy number variation (CNV), and single-nucleotide polymorphisms (SNPs). While each mechanism can influence gene expression substantially, the relative importance of each mechanism at the level of individual genes and tissues is poorly understood. Here, we present the integrative Models of Estimated gene expression (iModEst), which details the relative contribution of different regulators to the gene expression of 16,000 genes and 21 tissues within The Cancer Genome Atlas (TCGA). Specifically, we derive predictive models of gene expression using tumour data and test their predictive accuracy in cancerous and tumour-adjacent tissues. Our models can explain up to 70% of the variance in gene expression across 43% of the genes within both tumour and tumour-adjacent tissues. We confirm that TF expression best predicts gene expression in both tumour and tumour-adjacent tissue whereas methylation predictive models in tumour tissues does not transfer well to tumour adjacent tissues. We find new patterns and recapitulate previously reported relationships between regulator and gene-expression, such as CNV-predicted FGFR2 expression and SNP-predicted TP63 expression. Together, iModEst offers an interactive, comprehensive atlas of individual regulator-gene-tissue expression relationships as well as relationships between regulators.

ctDNA-based liquid biopsy reveals wider mutational profile with therapy resistance and metastasis susceptibility signatures in early-stage breast cancer patients

A minimally invasive analysis of plasma cell-free DNA (cfDNA) offers a genomic profiling of early-stage breast cancer (EBC), potentially identifying mutational signatures linked to metastasis and therapy resistance. In this study, paired plasma and tissue samples from 40 hormone receptor-positive (HR+) EBC patients were sequenced using a custom-designed comprehensive gene panel, OncoIndx. The genomic landscape of circulating tumor DNA (ctDNA) showed a broader mutation spectrum compared to tumor tissue DNA (tDNA), and provided reliable assessments of microsatellite instability (MSI), tumor mutation burden (TMB), homologous recombination deficiency (HRD), and loss of heterogeneity (LOH), all indicating high genomic instability. Importantly, early detection of estrogen receptor α (ESR1) mutations in ctDNA was achieved, highlighting its potential to identify patients at risk for endocrine resistance, a standard of care for HR + breast tumors. Mutations, particularly in DNA damage response (DDR) and proliferative signaling pathways (phosphatidyl inositol-4,5-bisphosphate 3-kinase; PIK3CA) suggest an increased risk of therapy resistance, pointing to opportunities for risk stratification and tailored treatment strategies in EBC. ctDNA-based liquid biopsy may provide minimally invasive comprehensive genomic analysis of EBC for identifying actionable targets and risk prediction for better disease management.

CSSEC: An adaptive approach integrating consensus and specific self-expressive coefficients for multi-omics cancer subtyping

Cancer is a complex and heterogeneous disease, and accurate cancer subtyping can significantly improve patient survival rates. The complexity of cancer spans multiple omics levels, and analyzing multi-omics data for cancer subtyping has become a major focus of research. However, extracting complementary information from different omics data sources and adaptively integrating them remains a major challenge. To address this, we proposed an adaptive approach integrating consensus and specific self-expressive coefficients for multi-omics cancer subtyping (CSSEC). First, independent self-expressive networks are applied to each omics to calculate coefficient matrices to measure patient similarity. Then, two feature graph convolutional network modules capture consensus and specific similarity features using the topK relevant features. Finally, the multi-omics self-expression coefficient matrix is constructed by consensus and specific similarity features. Furthermore, joint consistency and disparity constraints are applied to regularize the fusion of the self-expressive coefficients. Experimental results demonstrate that CSSEC outperforms existing state-of-the-art methods in survival analysis. Moreover, case studies on kidney cancer confirm that the cancer subtypes identified by CSSEC are biologically significant. The complete code can be available at https://github.com/ykxhs/CSSEC.

The multi-faceted roles of cancer-associated fibroblasts in pancreatic cancer

The tumor microenvironment (TME) has been linked with the pathogenesis of pancreatic ductal adenocarcinoma (PDAC), the most common histological subtype of pancreatic cancer. A central component of the TME are cancer-associated fibroblasts (CAFs), which can either suppress or promote tumor growth in a context-dependent manner. In this review, we will discuss the multi-faceted roles of CAFs in tumor-stroma interactions influencing cancer initiation, progression and therapeutic response.

ImmuneLENS characterizes systemic immune dysregulation in aging and cancer

Recognition and elimination of pathogens and cancer cells depend on the adaptive immune system. Thus, accurate quantification of immune subsets is vital for precision medicine. We present immune lymphocyte estimation from nucleotide sequencing (ImmuneLENS), which estimates T cell and B cell fractions, class switching and clonotype diversity from whole-genome sequencing data at depths as low as 5× coverage. By applying ImmuneLENS to the 100,000 Genomes Project, we identify genes enriched with somatic mutations in T cell-rich tumors, significant sex-based differences in circulating T cell fraction and demonstrated that the circulating T cell fraction in patients with cancer is significantly lower than in healthy individuals. Low circulating B cell fraction was linked to increased cancer incidence. Finally, circulating T cell abundance was more prognostic of 5-year cancer survival than infiltrating T cells.

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.

Precision medicine in colorectal cancer: genomics profiling and targeted treatment

Precision medicine has revolutionized the treatment of colorectal cancer by enabling a personalized approach tailored to each patient's unique genetic characteristics. Genomic profiling allows for the identification of specific mutations in genes such as KRAS, BRAF, and PIK3CA, which play a crucial role in cell signaling pathways that regulate cell proliferation, apoptosis, and differentiation. This information enables doctors to select targeted therapies that inhibit specific molecular pathways, maximizing treatment effectiveness and minimizing side effects. Precision medicine also facilitates adaptive monitoring of tumor progression, allowing for adjustments in therapy to maintain treatment effectiveness. While challenges such as high costs, limited access to genomic technology, and the need for more representative genomic data for diverse populations remain, collaboration between researchers, medical practitioners, policymakers, and the pharmaceutical industry is crucial to ensure that precision medicine becomes a standard of care accessible to all. With continued advances and support, precision medicine has the potential to improve treatment outcomes, reduce morbidity and mortality rates, and enhance the quality of life for colorectal cancer patients worldwide.

Recurrent ERBB2 alterations are associated with esophageal adenocarcinoma brain metastases

Brain metastases in esophageal adenocarcinoma (EAC) patients are associated with poor prognosis and remain understudied. We performed multi-omics analysis with whole-genome sequencing and single-cell spatial transcriptomics on the brain metastases and matched primary tumors. Our analysis identified ERBB2 as a recurrent oncogene in EAC brain metastases, with 9 out of 10 cases harboring amplifications. Single-cell whole-genome and multi-region sequencing revealed that ERBB2 alterations, occur early during disease progression and are associated with monoclonal seeding. Although the median survival in our cohort was 13 months, one patient on HER2 antibody-drug conjugate therapy remains a long-term survivor beyond 34 months. Interestingly, the sole patient without an ERBB2 alteration had JAK2 deletion, high T cell infiltration in the brain lesion, and survived 35 months after immune checkpoint therapy. Our findings have significant clinical implications for the treatment and management of EAC brain metastases.

Combining molecular characteristics and therapeutic analysis of PDOs predict clinical responses and guide PDAC personalized treatment

BACKGROUND

The emergence of targeted therapies and immunotherapy has broadened treatment options for patients with pancreatic ductal adenocarcinoma (PDAC). Despite this, traditional drug selection, predominantly relies on tumor markers and clinical staging, has underutilized these drugs due to ignoring patient genomic diversity. Patient-derived organoids (PDOs) and corresponding patient-derived organoid xenograft (PDOX) models offer a way to better understand and address this.

METHODS

In this study, we established PDOs and PDOX models from PDAC clinical samples. These models were analyzed using immunohistochemistry, H&E staining, and genomic profiling. Drug screening with 111 FDA-approved drugs was performed on PDOs, and drug responses in PDOs and PDOX models were compared to assess consistency with clinical treatment outcomes. Gene analysis was conducted to explore the molecular mechanisms underlying variations in drug responses. Additionally, by analyzing the sequencing results from various drug-sensitive groups, the identified differential gene-drug metabolism gene UGT1A10 were modulated in PDOs to evaluate its impact on drug efficacy. A co-culture system of PDOs with immune cells was developed to study the efficacy of immunotherapies.

RESULTS

PDOs and matched PDOX models retain the morphological, biological, and genomic characteristics of the primary tumor. Exome sequencing and RNA sequencing confirmed both the consistency and heterogeneity among the PDOs. High-throughput drug screening revealed significant variability in drug sensitivity across different organoids, yet PDOs and PDOX derived from the same patient exhibited a high degree of concordance in response to clinical chemotherapy agents. The gene expression analysis of PDOs with significant differences in drug sensitivity revealed UGT1A10 as a crucial regulator. The knockdown of UGT1A10 notably increased drug sensitivity. Furthermore, immune cells demonstrated specific cytotoxicity towards the organoids, underscoring the potential of the co-culture system for application in tumor immunotherapy.

CONCLUSION

Our results highlight the necessity for personalized treatment strategies that consider genomic diversity beyond tumor markers, thus validating the utility of PDOs and PDOX models in advancing PDAC research and personalized medicine.

RNA Transcripts Serve as a Template for Double-Strand Break Repair in Human Cells

Double-strand breaks (DSBs) are toxic lesions that lead to genome instability. While canonical DSB repair pathways typically operate independently of RNA, emerging evidence suggests that RNA:DNA hybrids and transcripts near damaged sites can influence repair outcomes. However, a direct role for transcript RNA as a template during DSB repair in human cells is yet to be established. In this study, we designed fluorescent- and sequencing-based assays, which demonstrated that RNA-containing oligonucleotides and messenger RNA serve as templates to promote DSB repair. We conducted a CRISPR/Cas9-based genetic screen to identify factors that promote RNA-templated DSB repair (RT-DSBR), and of the candidate polymerases, we identified DNA polymerase-zeta (Polζ) as the potential reverse transcriptase that facilitates RT-DSBR. Furthermore, by analyzing sequencing data from cancer genomes, we identified the presence of whole intron deletions, a unique genomic scar reflective of RT-DSBR activity generated when spliced mRNA serves as the repair template. These findings highlight RT-DSBR as an alternative pathway for repairing DSBs in transcribed genes, with potential mutagenic consequences.

The spatial landscape of cancer hallmarks reveals patterns of tumor ecological dynamics and drug sensitivity

Tumors are complex ecosystems of interacting cell types. The concept of cancer hallmarks distills this complexity into underlying principles that govern tumor growth. Here, we explore the spatial distribution of cancer hallmarks across 63 primary untreated tumors from 10 cancer types using spatial transcriptomics. We show that hallmark activity is spatially organized, with the cancer compartment contributing to the activity of seven out of 13 hallmarks, while the tumor microenvironment (TME) contributes to the activity of the rest. Additionally, we discover that genomic distance between tumor subclones correlates with differences in hallmark activity, even leading to clone-hallmark specialization. Finally, we demonstrate interdependent relationships between hallmarks at the junctions of TME and cancer compartments and how they relate to sensitivity to different neoadjuvant treatments in 33 bladder cancer patients from the DUTRENEO trial. In conclusion, our findings may improve our understanding of tumor ecology and help identify new drug biomarkers.

Synergistic RAS-MAPK and AKT Activation in MYC-Driven Tumors via Adjacent PVT1 Rearrangements

MYC-driven (MYC+) cancers are aggressive and often fatal. MYC dysregulation is a key event in these cancers, but overexpression of MYC alone is not always enough to cause cancer. Plasmocytoma Variant Translocation 1 (PVT1), a long non-coding RNA (lncRNA) adjacent to MYC on chromosome 8 is a rearrangement hotspot in many MYC+ cancers. In addition to being co-amplified with MYC, the genomic rearrangement at PVT1 involves translocation, which has had obscure functional consequences. We report that translocation at the PVT1 locus cause asymmetric enrichment of 5'-PVT1 and loss of 3'-PVT1. Despite being classified as a non-coding RNA, the retained 5' region of PVT1 generates a circular RNA (CircPVT1) that codes for the novel peptide we call Firefox (FFX). FFX augments AKT signaling and synergistically activates MYC and mTORC1 in these cells. Further, the 3' end of PVT1, which is lost during the translocation, codes for a tumor-suppressing micropeptide we named as Honeybadger (HNB). We demonstrate that HNB interacts with KRAS and disrupts the activation of KRAS effectors. Loss of HNB leads to activation of RAS/MAPK signaling pathway, and enhances MYC stability by promoting phosphorylation of MYC at Ser62. These findings identify PVT1 as a critical node that synchronizes MYC, AKT, and RAS-MAPK activities in cancer. Our study thus identifies a key mechanism by which rearrangements at the PVT1 locus activate additional oncogenic pathways that synergize with MYC to exacerbate the aggressiveness of MYC+ cancers. This newfound understanding explains the poor prognosis associated with MYC+ cancers and offers potential therapeutic targets that could be leveraged in treatment strategies for these cancers.

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.

Application of Next-Generation Sequencing to Realize Principles of Precision Therapy in Management of Cancer Patients

All cancers are diseases of the genome, since the cancer cell genome typically consists of 10,000s of passenger alterations, 5-10 biologically relevant alterations, and 1-2 "actionable" alterations. Therefore, somatic mutations in cancer cells can have diagnostic, prognostic, and predictive value. Traditional methods are widely used for testing, such as immunohistochemistry, Sanger sequencing, and allele-specific PCR. However, due to the low throughput, these methods are focused exclusively on testing the most common mutations in target genes. The modern next generation sequencing (NGS) is a technology that enables precision oncology in its current form. ESCAT and ESMO Guidelines defined NGS for routine use in patients with advanced cancers such as non-squamous non-small cell lung cancer, prostate cancer, ovarian cancer, and cholangiocarcinoma. The high sensitivity of the NGS method allows it to be used to search for specific mutations in circulating tumor DNA in blood plasma and other body fluids. NGS testing has evolved from hotspot panels, actionable gene panels, and disease-specific panels to more comprehensive panels. The exome and whole genome sequencing approaches are just beginning to emerge, that is why panel-based testing remains most optimal in oncology practice. NGS is also widely used to identify new and rare mutations in cancer genes and detect inherited cancer mutations.

An MGRN1-Based Biomarker Combination Accurately Predicts Melanoma Patient Survival

With ever-increasing incidence and high metastatic potential, cutaneous melanoma is the deadliest skin cancer. Risk prediction based on the Tumor-Node-Metastasis (TNM) staging system has medium accuracy with intermediate IIB-IIIB stages, as roughly 25% of patients with low-medium-grade TNM, and hence a favorable prognostic, undergo an aggressive disease with short survival and around 15% of deaths arise from metastases of thin, low-risk lesions. Therefore, reliable prognostic biomarkers are required. We used genomic and clinical information of melanoma patients from the TCGA-SKCM cohort and two GEO studies for discovery and validation of potential biomarkers, respectively. Neither mutation nor overexpression of major melanoma driver genes provided significant prognostic information. Conversely, expression of MGRN1 and the melanocyte-specific genes MLANA, PMEL, and TYRP1 provided a simple 4-gene signature identifying with high-sensitivity (>80%), low-medium TNM patients with adverse outcomes. Transcriptomic analysis of tumors with this signature, or from low-medium-grade TNM patients with poor outcomes, revealed comparable dysregulation of an inflammatory response, cell cycle progression, and DNA damage/repair programs. A functional analysis of MGRN1-knockout cells confirmed these molecular features. Therefore, the simple MGRN1-MLANA-PMEL-TYRP1 combination of biomarkers complemented TNM staging prognostic accuracy and pointed to the dysregulation of immunological responses and genomic stability as determinants of a melanoma outcome.

Identification of nonsense-mediated decay inhibitors that alter the tumor immune landscape

Despite exciting developments in cancer immunotherapy, its broad application is limited by the paucity of targetable antigens on the tumor cell surface. As an intrinsic cellular pathway, nonsense-mediated decay (NMD) conceals neoantigens through the destruction of the RNA products from genes harboring truncating mutations. We developed and conducted a high-throughput screen, based on the ratiometric analysis of transcripts, to identify critical mediators of NMD in human cells. This screen implicated disruption of kinase SMG1's phosphorylation of UPF1 as a potential disruptor of NMD. This led us to design a novel SMG1 inhibitor, KVS0001, that elevates the expression of transcripts and proteins resulting from human and murine truncating mutations in vitro and murine cells in vivo. Most importantly, KVS0001 concomitantly increased the presentation of immune-targetable human leukocyte antigens (HLA) class I-associated peptides from NMD-downregulated proteins on the surface of human cancer cells. KVS0001 provides new opportunities for studying NMD and the diseases in which NMD plays a role, including cancer and inherited diseases.

Nonstop mutations cause loss of renal tumor suppressor proteins VHL and BAP1 and affect multiple stages of protein translation

Nonstop extension or stop-loss mutations lead to the extension of a protein at its carboxyl terminus. Recently, nonstop mutations in the tumor suppressor SMAD Family Member 4 (SMAD4) have been discovered to lead to proteasomal SMAD4 degradation. However, this mutation type has not been studied in other cancer genes. Here, we explore somatic nonstop mutations in the tumor suppressor genes BRCA1 Associated Protein 1 (BAP1) and Von Hippel-Lindau (VHL) enriched in renal cell carcinoma. For BAP1, nonstop mutations generate an extremely long extension. Instead of proteasomal degradation, the extension decreases translation and depletes BAP1 messenger RNA from heavy polysomes. For VHL, the short extension leads to proteasomal degradation. Unexpectedly, the mutation alters the selection of the translational start site shifting VHL isoforms. We identify germline VHL nonstop mutations in patients leading to the early onset of severe disease manifestations. In summary, nonstop extension mutations inhibit the expression of renal tumor suppressor genes with pleiotropic effects on translation and protein stability.

Single-cell DNA sequencing reveals pervasive positive selection throughout preleukemic evolution

The representation of driver mutations in preleukemic hematopoietic stem cells (pHSCs) provides a window into the somatic evolution that precedes acute myeloid leukemia (AML). Here, we isolate pHSCs from the bone marrow of 16 patients diagnosed with AML and perform single-cell DNA sequencing on thousands of cells to reconstruct phylogenetic trees of the major driver clones in each patient. We develop a computational framework that can infer levels of positive selection operating during preleukemic evolution from the statistical properties of these phylogenetic trees. Combining these data with 67 previously published phylogenetic trees, we find that the highly variable structures of preleukemic trees emerge naturally from a simple model of somatic evolution with pervasive positive selection typically in the range of 9%-24% per year. At these levels of positive selection, we show that the identification of early multiple-mutant clones could be used to identify individuals at risk of future AML.

Genomic hallmarks of endocrine therapy resistance in ER/PR+HER2- breast tumours

ER/PR+HER2- breast tumours are the most predominant subtype of breast cancer worldwide, including India. Unlike TNBCs, these tumours can be treated with anti-estrogens or aromatase inhibitors. Despite the success of endocrine therapy, a fraction of patients with ER/PR+ breast tumours do not respond to hormone-receptor-specific treatment and encounter disease recurrence contributing to their poor survival. The genomic underpinnings of therapy resistance in ER/PR+HER2- breast tumours are incompletely understood. We have performed whole genome sequencing (WGS) from tumour and normal tissue samples from endocrine-therapy resistant ER/PR+HER2- breast cancer patients who have relapsed on endocrine therapy and have conducted a comparative analysis of WGS data generated from tissues of endocrine therapy sensitive patients who remained free of disease during a minimum 5-year follow-up. Our analysis shows (a) a three-gene (PIK3CA-ESR1-TP53) resistance signature, and (b) impaired DNA double-strand break repair and homologous recombination pathways, were significantly associated with endocrine-therapy resistance and disease recurrence in ER/PR+HER2- tumours. Genome instability, contributing to high burden of copy-number, structural alterations and telomere-shortening identified as major markers of endocrine treatment resistance. Early prediction of endocrine-therapy resistance from the genomic landscape of breast tumours will aid therapeutics. Our finding also opens up the possibility of repurposing PARP inhibitors in treating endocrine therapy-resistant breast cancer patients.

FuSViz-visualization and interpretation of structural variation using cancer genomics and transcriptomics data

Structural variation (SV) is a frequent category of genetic alterations important for understanding cancer genome evolution and revealing key cancer driver events. With the development of high-throughput sequencing technologies, the ability to detect SVs of various sizes and types has improved, at both the DNA and RNA levels. However, SV calls are still prone to a considerable fraction of false positives, which necessitates visual inspection and manual curation as part of the quality control process. Identification of reliable and recurrent SVs in larger cohorts lends strength to revealing the driving roles of SVs in cancer development and to the discovery of potential diagnostic and prognostic biomarkers. Here, we present FuSViz, an application for visualization, interpretation, and prioritization of SVs. The tool provides multiple data view approaches in a user-friendly interface, allowing the investigation of prevalence and recurrence of SVs and relevant partner genes in a sample cohort. It integrates SV calls from DNA and RNA sequencing datasets to comprehensively illustrate the biological impact of SVs on the implicated genes and associated genomic regions. The functionality of FuSViz is intended for interrogation of both recurrent and private SVs, effectively assisting with pathogenicity evaluation and biomarker discovery in cancer sequencing projects.

Bone marrow breakout lesions act as key sites for tumor-immune cell diversification in multiple myeloma

The bone marrow microenvironment plays a crucial role in the development of multiple myeloma. As the disease progresses, malignant myeloma cells can evolve to survive outside the bone marrow. However, the processes underlying bone marrow independence and their consequences for immune control remain poorly understood. Here, we conducted single-cell and spatial multiomics analyses of bone marrow-confined intramedullary disease and paired breakout lesions that disrupt the cortical bone. These analyses revealed a distinct cellular microenvironment and architectural features of breakout lesions, characterized by extensive areas of malignant plasma cells interspersed with lesion-specific solitary natural killer and macrophage populations, as well as focal accumulations of immune cell agglomerates. Within these agglomerates, spatially confined T cell clones expanded alongside various immune cells, coinciding with the local genomic evolution of tumor cells. These analyses identify breakout lesions as a hotspot for tumor-immune cell interactions and diversification, representing a key event in myeloma pathogenesis.

PA2G4 in health and disease: An underestimated multifunctional regulator

BACKGROUND

Proliferation-associated protein 2G4 (PA2G4), also known as ErbB3-binding protein 1 (EBP1), is an evolutionarily conserved, ubiquitously expressed, multifunctional factor in health and disease. In recent decades, its role as a sophisticated regulator in a broad range of biological processes has drawn widespread attention from researchers.

AIM OF REVIEW

We introduce the molecular structure, functional modules, and post-translational modifications of PA2G4. We further elaborate on its role and function in immune microenvironment modulation, cell growth, neural homeostasis and embryonic development. In particular, we summarize its relevance to tumorigenesis and cancer progression and describe its molecular mechanisms in regulating the hallmarks of cancers. This review aims to provide a comprehensive blueprint of PA2G4 functions and to inspire further basic and translational studies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Owing to its versatile domains and motifs, PA2G4 regulates a variety of molecular processes, including transcription, translation, proteostasis and epigenetic modulation, suggesting its critical roles in maintaining homeostasis. There are two isoforms of the PA2G4 protein: PA2G4-p42 and PA2G4-p48. While both isoforms regulate cellular activities, they often exert distinct or even contradictory effects. Dysfunction and aberrant expression of PA2G4 isoforms lead to the occurrence and progression of various diseases, indicating their role as predictive markers or therapeutic targets.

Heterochromatin fidelity is a therapeutic vulnerability in lymphoma and other human cancers

Genes involved in the regulation of chromatin structure are frequently disrupted in cancer, contributing to an aberrant transcriptome and phenotypic plasticity. Yet, therapeutics targeting mutant forms of chromatin-modifying enzymes have yielded only modest clinical utility, underscoring the difficulty of targeting the epigenomic underpinnings of aberrant gene regulatory networks. Here, we sought to identify novel epigenetic vulnerabilities in diffuse large B-cell lymphoma (DLBCL). Through phenotypic screens and biochemical analysis, we demonstrated that inhibition of the H3K9 demethylases KDM4A and KDM4C elicits potent, subtype-agnostic cytotoxicity by antagonizing transcriptional networks associated with B-cell identity and epigenetically rewiring heterochromatin. KDM4 demethylases associated with the KRAB zinc finger ZNF587, and their enzymatic inhibition led to DNA replication stress and DNA damage-einduced cGAS-STING activation. Broad surveys of transcriptional data from patients also revealed KDM4 family dysregulation in several other cancer types. To explore this potential therapeutic avenue, we performed high-throughput small molecule screens with H3K9me3 nucleosome substrates and identified novel KDM4 demethylase inhibitors. AI-guided protein-ligand binding predictions suggested diverse modes of action for various small molecule hits. Our findings underscore the relevance of targeting fundamental transcriptional and epigenetic mechanisms for anti-cancer therapy.

Role of silent mutations in KRAS -mutant tumors

ABSTRACT

Silent mutations within the RAS  gene have garnered increasing attention for their potential roles in tumorigenesis and therapeutic strategies. Kirsten-RAS ( KRAS ) mutations, predominantly oncogenic, are pivotal drivers in various cancers. While extensive research has elucidated the molecular mechanisms and biological consequences of active KRAS  mutations, the functional significance of silent mutations remains relatively understudied. This review synthesizes current knowledge on KRAS  silent mutations, highlighting their impact on cancer development. Silent mutations, which do not alter protein sequences but can affect RNA stability and translational efficiency, pose intriguing questions regarding their contribution to tumor biology. Understanding these mutations is crucial for comprehensively unraveling KRAS -driven oncogenesis and exploring novel therapeutic avenues. Moreover, investigations into the clinical implications of silent mutations in KRAS -mutant tumors suggest potential diagnostic and therapeutic strategies. Despite being in early stages, research on KRAS  silent mutations holds promise for uncovering novel insights that could inform personalized cancer treatments. In conclusion, this review underscores the evolving landscape of KRAS  silent mutations, advocating for further exploration to bridge fundamental biology with clinical applications in oncology.

Combinatorial In Vivo Genome Editing Identifies Widespread Epistasis and an Accessible Fitness Landscape During Lung Tumorigenesis

Lung adenocarcinoma, the most common subtype of lung cancer, is genomically complex, with tumors containing tens to hundreds of non-synonymous mutations. However, little is understood about how genes interact with each other to enable the evolution of cancer in vivo, largely due to a lack of methods for investigating genetic interactions in a high-throughput and quantitative manner. Here, we employed a novel platform to generate tumors with inactivation of pairs of ten diverse tumor suppressor genes within an autochthonous mouse model of oncogenic KRAS-driven lung cancer. By quantifying the fitness of tumors with every single and double mutant genotype, we show that most tumor suppressor genetic interactions exhibited negative epistasis, with diminishing returns on tumor fitness. In contrast, Apc inactivation showed positive epistasis with the inactivation of several other genes, including synergistic effects on tumor fitness in combination with Lkb1 or Nf1 inactivation. Sign epistasis was extremely rare, suggesting a surprisingly accessible fitness landscape during lung tumorigenesis. These findings expand our understanding of the interactions that drive tumorigenesis in vivo.

Chromothripsis in cancer

Chromothripsis is a mutational phenomenon in which a single catastrophic event generates extensive rearrangements of one or a few chromosomes. This extreme form of genome instability has been detected in 30-50% of cancers. Studies conducted in the past few years have uncovered insights into how chromothripsis arises and deciphered some of the cellular and molecular consequences of chromosome shattering. This Review discusses the defining features of chromothripsis and describes its prevalence across different cancer types as indicated by the manifestations of chromothripsis detected in human cancer samples. The different mechanistic models of chromothripsis, derived from in vitro systems that enable causal inference through experimental manipulation, are discussed in detail. The contribution of chromothripsis to cancer development, the selective advantages that cancer cells might gain from chromothripsis, the evolutionary trajectories of chromothriptic tumours, and the potential vulnerabilities and therapeutic opportunities presented by chromothriptic cells are also highlighted.

Genome-scale models in human metabologenomics

Metabologenomics integrates metabolomics with other omics data types to comprehensively study the genetic and environmental factors that influence metabolism. These multi-omics data can be incorporated into genome-scale metabolic models (GEMs), which are highly curated knowledge bases that explicitly account for genes, transcripts, proteins and metabolites. By including all known biochemical reactions catalysed by enzymes and transporters encoded in the human genome, GEMs analyse and predict the behaviour of complex metabolic networks. Continued advancements to the scale and scope of GEMs - from cells and tissues to microbiomes and the whole body - have helped to design effective treatments and develop better diagnostic tools for metabolic diseases. Furthermore, increasing amounts of multi-omics data are incorporated into GEMs to better identify the underlying mechanisms, biomarkers and potential drug targets of metabolic diseases.

Leptomeningeal metastatic disease: new frontiers and future directions

Leptomeningeal metastatic disease (LMD), encompassing entities of 'meningeal carcinomatosis', neoplastic meningitis' and 'leukaemic/lymphomatous meningitis', arises secondary to the metastatic dissemination of cancer cells from extracranial and certain intracranial malignancies into the leptomeninges and cerebrospinal fluid. The clinical burden of LMD has been increasing secondary to more sensitive diagnostics, aggressive local therapies for discrete brain metastases, and improved management of extracranial disease with targeted and immunotherapeutic agents, resulting in improved survival. However, owing to drug delivery challenges and the unique microenvironment of LMD, novel therapies against systemic disease have not yet translated into improved outcomes for these patients. Underdiagnosis and misdiagnosis are common, response assessment remains challenging, and the prognosis associated with this disease of whole neuroaxis remains extremely poor. The dearth of effective therapies is further challenged by the difficulties in studying this dynamic disease state. In this Review, a multidisciplinary group of experts describe the emerging evidence and areas of active investigation in LMD and provide directed recommendations for future research. Drawing upon paradigm-changing advances in mechanistic science, computational approaches, and trial design, the authors discuss domain-specific and cross-disciplinary strategies for optimizing the clinical and translational research landscape for LMD. Advances in diagnostics, multi-agent intrathecal therapies, cell-based therapies, immunotherapies, proton craniospinal irradiation and ongoing clinical trials offer hope for improving outcomes for patients with LMD.

Uridine-cytidine kinase 2 is correlated with immune, DNA damage repair and promotion of cancer stemness in pan-cancer

Background

UCK2 (Uridine-Cytidine Kinase 2) is a promising prognostic marker for malignant tumors, but its association with immune infiltration and cancer stemness in pan-cancer remains to be fully understood. we find that gene UCK2 is closed related to RNA stemness scores (RNAss) and DNA stemness scores (DNAss), which is measured the tumor stemness. We also discover an association between UCK2 expression and immune cells by CIBERSORT algorithm, ESTIMATE algorithm and ssGSEA algorithm, especially, related to T cell, monocytes, mast cells, and macrophages. This study aims to shed light on the role and possible mechanism of UCK2 in pan-cancer.

Methods

We used the R programming language for pan-cancer bulk sequencing data analysis, which were obtained from the University of California, Santa Cruz (UCSC) datasets. UCSC database is a very useful for explore data from TCGA and other cancer genomics datasets, The data we explored at the UCK2 transcriptome level came from TCGA data in the UCSC database. We explored differential UCK2 expression between tumor and normal samples. Immunohistochemistry (IHC) was utilized to validate the expression of UCK2 in different types cancers using tumor tissue chips. The correlations of UCK2 with prognosis, genetic instability, DNA repair, cancer stem cell characteristics, and immune cell infiltration were investigated. Furthermore, single-cell datasets, acquired from the Gene Expression Omnibus (GEO) database, were used to validate the relationship between UCK2 and immune cells. GEO is a famous public genomics database supporting freely disseminates microarray data. Finally, we analyzed the correlation between UCK2 and drug sensitivity.

Results

UCK2 expression was observed to be high in most cancers and was remarkably related to the prognosis of pan-cancers. We found that the increased UCK2 expression was associated with higher genetic instability. Additionally, positive relationships were observed between UCK2 expression and mismatch repair genes, homologous recombination repair genes, and cancer stemness across different cancer types. There were significant correlations between UCK2 and T cells, monocytes, mast cells, and macrophages. Moreover, as expected, the immune checkpoint human leucocyte antigen (HLA) was found to be negatively related to UCK2. Similarly, UCK2 was also observed to have a negative association with major histocompatibility complex (MHC) genes. We noted that UCK2 had significant correlations with the sensitivity to various anti-cancer drug.

Conclusion

We have observed that UCK2 plays pivotal roles in prognosis and tumor immunity, and it is associated with DNA repair and cancer stemness. The UCK2 gene exhibits a strong correlation with the immune checkpoints HLA. This study highlights its potential impact on drug sensitivity.

Intratumor heterogeneity of HPV integration in HPV-associated head and neck cancer

Integration of human papillomavirus (HPV) into the host genome drives HPV-positive head and neck squamous cell carcinoma (HPV+ HNSCC). Whole-genome sequencing of 51 tumors revealed intratumor heterogeneity of HPV integration, with 44% of breakpoints subclonal, and a biased distribution of integration breakpoints across the HPV genome. Four HPV physical states were identified, with at least 49% of tumors progressing without integration. HPV integration was associated with APOBEC-induced broad genomic instability and focal genomic instability, including structural variants at integration sites. HPV+ HNSCCs exhibited almost no smoking-induced mutational signatures. Heterozygous loss of ataxia-telangiectasia mutated (ATM) was observed in 67% of tumors, with its downregulation confirmed by single-cell RNA sequencing and immunohistochemistry, suggesting ATM haploinsufficiency contributes to carcinogenesis. PI3K activation was the major oncogenic mutation, with JAK-STAT activation in tumors with clonal integration and NF-kappa B activation in those without. These findings provide valuable insights into HPV integration in HPV+ HNSCC.

Comprehensive single-cell pan-cancer atlas unveils IFI30+ macrophages as key modulators of intra-tumoral immune dynamics

Background

The convergence of macrophage-targeted strategies with immune checkpoint blockade therapies defines a pivotal avenue in contemporary tumor therapy. Identifying robust genetic regulators in this context is imperative.

Methods

This study elucidates IFI30's role in enhancing Major Histocompatibility Complex II (MHC-II) restriction antigen processing. Despite its recognition in cancer immunotherapy, IFI30 remains a nascent focus. Our approach involves a multi-omics analysis of IFI30 tumor immunological profile in the macrophage-mediated Tumor Microenvironment (TME), spanning various cancers and bolstered by rigorous co-culture laboratory work.

Results

IFI30 predominantly localizes in monocyte/macrophage populations, correlating strongly with immune cell infiltration. Substantiated by single-cell analysis, IFI30 exhibits significant functional enrichment in immune-related pathways. Co-expression with immune-related genes, including MHC elements and immune checkpoints, further validates its relevance.

Conclusion

Our study positions IFI30 as a promising immunotherapeutic target. Pan-cancer analyses and glioblastoma multiforme (GBM) investigations collectively underscore IFI30's potential as a TME modulator, particularly in its interaction with M2-macrophages. IFI30 emerges as a prospective intervention point in the immunotherapeutic landscape.

Ongoing chromothripsis underpins osteosarcoma genome complexity and clonal evolution

Osteosarcoma is the most common primary cancer of the bone, with a peak incidence in children and young adults. Using multi-region whole-genome sequencing, we find that chromothripsis is an ongoing mutational process, occurring subclonally in 74% of osteosarcomas. Chromothripsis generates highly unstable derivative chromosomes, the ongoing evolution of which drives the acquisition of oncogenic mutations, clonal diversification, and intra-tumor heterogeneity across diverse sarcomas and carcinomas. In addition, we characterize a new mechanism, termed loss-translocation-amplification (LTA) chromothripsis, which mediates punctuated evolution in about half of pediatric and adult high-grade osteosarcomas. LTA chromothripsis occurs when a single double-strand break triggers concomitant TP53 inactivation and oncogene amplification through breakage-fusion-bridge cycles. It is particularly prevalent in osteosarcoma and is not detected in other cancers driven by TP53 mutation. Finally, we identify the level of genome-wide loss of heterozygosity as a strong prognostic indicator for high-grade osteosarcoma.

Tobacco smoke carcinogens exacerbate APOBEC mutagenesis and carcinogenesis

Mutations in somatic cells are inflicted by both extrinsic and intrinsic sources and contribute over time to cancer. Tobacco smoke contains chemical carcinogens that have been causatively implicated with cancers of the lung and head & neck1,2. APOBEC family DNA cytosine deaminases have emerged as endogenous sources of mutation in cancer, with hallmark mutational signatures (SBS2/SBS13) that often co-occur in tumors of tobacco smokers with an equally diagnostic mutational signature (SBS4)3,4. Here we challenge the dogma that mutational processes are thought to occur independently and with additive impact by showing that 4-nitroquinoline 1-oxide (NQO), a model carcinogen for tobacco exposure, sensitizes cells to APOBEC3B (A3B) mutagenesis and leads to synergistic increases in both SBS2 mutation loads and oral carcinomas in vivo. NQO-exposed/A3B-expressing animals exhibit twice as many head & neck lesions as carcinogen-exposed wildtype animals. This increase in carcinogenesis is accompanied by a synergistic increase in mutations from APOBEC signature SBS2, but not from NQO signature SBS4. Interestingly, a large proportion of A3B-catalyzed SBS2 mutations occurs as strand-coordinated pairs within 32 nucleotides of each other in transcribed regions, suggesting a mechanism in which removal of NQO-DNA adducts by nucleotide excision repair exposes short single-stranded DNA tracts to enzymatic deamination. These highly enriched pairs of APOBEC signature mutations are termed didyma (Greek for twins) and are mechanistically distinct from other types of clustered mutation (omikli and kataegis). Computational analyses of lung and head & neck tumor genomes show that both APOBEC mutagenesis and didyma are elevated in cancers from smokers compared to non-smokers. APOBEC signature mutations and didyma are also elevated in normal lung tissues in smokers prior to cancer initiation. Collectively, these results indicate that DNA adducting mutagens in tobacco smoke can amplify DNA damage and mutagenesis by endogenous APOBEC enzymes and, more broadly, suggest that mutational mechanisms can interact synergistically in both cancer initiation and promotion.

Research Trends and Development Dynamics of qPCR-based Biomarkers: A Comprehensive Bibliometric Analysis

Quantitative polymerase chain reaction (qPCR) is a vital molecular technique for biomarker detection; however, its clinical application is impeded by the scarcity of robust biomarkers and the inherent limitations of the technology. This study conducted a bibliometric analysis of 4063 qPCR-based biomarker studies sourced from the Web of Science (WOS) database, employing VOSviewer and CiteSpace to generate multi-dimensional structural insights into this field. The results reveal a growing trend in research within this domain, with gene expression analysis playing a central role in the identification of potential biomarkers. Among these, cancer-related biomarkers are the most prominent, while research on biomarkers for other diseases remains limited. Liquid biopsy biomarkers, including microRNA (miRNA), circulating free DNA (cfDNA), and circulating tumor DNA (ctDNA), are increasingly being explored. The integration of bioinformatics, omics analysis, and high-throughput technologies with qPCR is accelerating biomarker discovery. Furthermore, large-scale parallel sequencing is emerging as a potential alternative to relative quantification and microarray techniques. Nevertheless, qPCR remains essential for validating specific biomarkers, and further standardization of its protocols is necessary to enhance reliability. This study provides a systematic analysis of qPCR-based biomarker research and underscores the need for future technological integration and standardization to facilitate broader clinical applications.

RPRD1B's direct interaction with phosphorylated RNA polymerase II regulates polyadenylation of cell cycle genes and drives cancer progression

RNA polymerase II (Pol II) regulates eukaryotic gene expression through dynamic phosphorylation of its C-terminal domain (CTD). Phosphorylation at Ser2 and Thr4 on the CTD is crucial for RNA 3' end processing and facilitating the recruitment of cleavage and termination factors. However, the transcriptional roles of most CTD-binding proteins remain poorly understood. In this study, we focus on RPRD1B, a transcriptional regulator that interacts with the phosphorylated CTD and has been implicated in various cancers. We investigated its molecular mechanism during transcription and found that RPRD1B modulates alternative polyadenylation of cell growth transcripts by directly interacting with the CTD. RPRD1B is recruited to transcribing Pol II near the 3' end of the transcript, specifically in response to Ser2 and Thr4 phosphorylation, but only after flanking Ser5 phosphorylation is removed. Transcriptomic analysis of RPRD1B knockdown cells revealed its role in cell proliferation via termination of the key cell growth genes at upstream polyadenylation sites, leading to the production of tumor suppressor transcripts that lack AU-rich elements (AREs) with increased mRNA stability. Overall, our study uncovers previously unrecognized connections between the Pol II CTD and CID, highlighting their influence on 3' end processing and their contribution to abnormal cell growth in cancer.

Evolutionary trajectories of immune escape across cancers

Immune escape is a critical hallmark of cancer progression and underlies resistance to multiple immunotherapies. However, it remains unclear when the genetic events associated with immune escape occur during cancer development. Here, we integrate functional genomics studies of immunomodulatory genes with a tumor evolution reconstruction approach to infer the evolution of immune escape across 38 cancer types from the Pan-Cancer Analysis of Whole Genomes dataset. Different cancers favor mutations in different immunomodulatory pathways. For example, the antigen presentation machinery is highly mutated in colorectal adenocarcinoma, lung squamous cell carcinoma, and chromophobe renal cell carcinoma, and the protein methylation pathway is highly mutated in bladder transitional cell carcinoma and lung adenocarcinoma. We also observe different timing patterns in multiple immunomodulatory pathways. For instance, mutations impacting genes involved in cellular amino acid metabolism were more likely to happen late in pancreatic adenocarcinoma. Mutations in the glucocorticoid receptor regulatory network pathway tended to occur early, while mutations in the TNF pathways were more likely to occur late in B-cell non-Hodgkin lymphoma. Mutations in the NOD1/2 signaling pathway and DNA binding transcription factor activity tended to happen late in breast adenocarcinoma and ovarian adenocarcinoma. Together, these results delineate the evolutionary trajectories of immune escape in different cancer types and highlight opportunities for improved immunotherapy of cancer.

p53 mutation biases squamocolumnar junction progenitor cells towards dysplasia rather than metaplasia in Barrett's oesophagus

BACKGROUND

While p53 mutations occur early in Barrett's oesophagus (BE) progression to oesophageal adenocarcinoma (EAC), their role in gastric cardia stem cells remains unclear.

OBJECTIVE

This study investigates the impact of p53 mutation on the fate and function of cardia progenitor cells in BE to EAC progression, particularly under the duress of chronic injury.

DESIGN

We used a BE mouse model (L2-IL1β) harbouring a Trp53 mutation (R172H) to study the effects of p53 on Cck2r+ cardia progenitor cells. We employed lineage tracing, pathological analysis, organoid cultures, single-cell RNA sequencing (scRNA-seq) and computational analyses to investigate changes in progenitor cell behaviour, differentiation patterns and tumour progression. Additionally, we performed orthotopic transplantation of sorted metaplastic and mutant progenitor cells to assess their tumourigenic potential in vivo.

RESULTS

The p53 mutation acts as a switch to expand progenitor cells and inhibit their differentiation towards metaplasia, but only amidst chronic injury. In L2-IL1β mice, p53 mutation increased progenitors expansion and lineage-tracing with a shift from metaplasia to dysplasia. scRNA-seq revealed dysplastic cells arise directly from mutant progenitors rather than progressing through metaplasia. In vitro, p53 mutation enhanced BE progenitors' organoid-forming efficiency, growth, DNA damage resistance and progression to aneuploidy. Sorted metaplastic cells grew poorly with no progression to dysplasia, while mutant progenitors gave rise to dysplasia in orthotopic transplantation. Computational analyses indicated that p53 mutation inhibited stem cell differentiation through Notch activation.

CONCLUSIONS

p53 mutation contributes to BE progression by increasing expansion and fitness of undifferentiated cardia progenitors and preventing their differentiation towards metaplasia.

Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes

BACKGROUND

Genetic studies have associated thousands of enhancers with breast cancer (BC). However, the vast majority have not been functionally characterized. Thus, it remains unclear how BC-associated enhancers contribute to cancer.

RESULTS

Here, we perform single-cell CRISPRi screens of 3513 regulatory elements associated with breast cancer to measure the impact of these regions on transcriptional phenotypes. Analysis of > 500,000 single-cell transcriptomes in two breast cancer cell lines shows that perturbation of BC-associated enhancers disrupts breast cancer gene programs. We observe BC-associated enhancers that directly or indirectly regulate the expression of cancer genes. We also find one-to-multiple and multiple-to-one network motifs where enhancers indirectly regulate cancer genes. Notably, multiple BC-associated enhancers indirectly regulate TP53. Comparative studies illustrate subtype specific functions between enhancers in ER + and ER - cells. Finally, we develop the pySpade package to facilitate analysis of single-cell enhancer screens.

CONCLUSIONS

Overall, we demonstrate that enhancers form regulatory networks that link cancer genes in the genome, providing a more comprehensive understanding of the contribution of enhancers to breast cancer development.

Molecular tumor board: molecularly adjusted therapy upon identification and functional validation of a novel ALK resistance mutation in a case of lung adenocarcinoma

We report a case of a long-term surviving patient with EML4/ALK translocated non-small cell adenocarcinoma of the lung in UICC8 stage IVA. During recurrence under continuous crizotinib therapy, a hitherto insufficiently characterized missense mutation in the ALK gene (Arg1181His) was identified through targeted sequencing. The aforementioned EML4/ALK translocation could still be detected in this situation. Employing a 3D reconstruction of the ALK tertiary structure, considering its interaction with various ALK inhibitors at the molecular binding site, our analysis indicated the presence of a mutation associated with crizotinib resistance. To validate the biological relevance of this previously unknown mutation, we carried out an in vitro validation approach in cell culture in addition to the molecular diagnostics accompanied by the molecular tumor board. The tumor scenario was mimicked through retroviral transfection. Our comparative in vitro treatment regimen paired with the clinical trajectory of the patient, corroborated our initial clinical and biochemical suspicions. Our approach demonstrates preclinical, in silico, and clinical evidence of a novel crizotinib resistance mutation in ALK as well as sensitivity toward brigatinib and potentially lorlatinib. In future cases, this procedure represents an important contribution to functional diagnostics in the context of molecular tumor boards.

Single-cell and bulk RNA sequencing analysis reveals CENPA as a potential biomarker and therapeutic target in cancers

BACKGROUND

Cancer remains one of the most significant public health challenges worldwide. A widely recognized hallmark of cancer is the ability to sustain proliferative signaling, which is closely tied to various cell cycle processes. Centromere Protein A (CENPA), a variant of the standard histone H3, is crucial for selective chromosome segregation during the cell cycle. Despite its importance, a comprehensive pan-cancer bioinformatic analysis of CENPA has not yet been conducted.

METHODS

Data on genomes, transcriptomes, and clinical information were retrieved from publicly accessible databases. We analyzed CENPA's genetic alterations, mRNA expression, functional enrichment, association with stemness, mutations, expression across cell populations and cellular locations, link to the cell cycle, impact on survival, and its relationship with the immune microenvironment. Additionally, a prognostic model for glioma patients was developed to demonstrate CENPA's potential as a biomarker. Furthermore, drugs targeting CENPA in cancer cells were identified and predicted using drug sensitivity correlations and protein-ligand docking.

RESULTS

CENPA exhibited low levels of gene mutation across various cancers. It was found to be overexpressed in nearly all cancer types analyzed in TCGA, relative to normal controls, and was predominantly located in the nucleus of malignant cells. CENPA showed a strong association with the cancer cell cycle, particularly as a biomarker for the G2 phase. It also emerged as a valuable diagnostic and prognostic biomarker across multiple cancer types. In glioma, CENPA demonstrated reliable prognostic potential when used alongside other prognostic factors. Additionally, CENPA was linked to the immune microenvironment. Drugs such as CD-437, 3-Cl-AHPC, Trametinib, BI-2536, and GSK461364 were predicted to target CENPA in cancer cells.

CONCLUSION

CENPA serves as a crucial biomarker for the cell cycle in cancers, offering both diagnostic and prognostic value.

Community assembly modeling of microbial evolution within Barrett's esophagus and esophageal adenocarcinoma

Mathematical modeling of somatic evolution, a process impacting both host cells and microbial communities in the human body, can capture important dynamics driving carcinogenesis. Here we considered models for esophageal adenocarcinoma (EAC), a cancer that has dramatically increased in incidence over the past few decades in Western populations, with high case fatality rates due to late-stage diagnoses. Despite advancements in genomic analyses of the precursor Barrett's esophagus (BE), prevention of late-stage EAC remains a significant clinical challenge. Previous microbiome studies in BE and EAC have focused on quantifying static microbial abundance differences rather than evolutionary dynamics. Using whole genome sequencing data from esophageal tissues, we first applied a robust bioinformatics pipeline to extract non-host DNA reads, mapped these putative reads to microbial taxa, and retained those taxa with high genomic coverage. When applying mathematical models of microbial evolution to sequential stages of progression to EAC, we observed evidence of neutral dynamics in community assembly within normal esophageal tissue and BE, but not EAC. In a case-control study of BE patients who progressed to EAC cancer outcomes (CO) versus those who had non-cancer outcomes (NCO) during follow-up (mean=10.5 years), we found that Helicobacter pylori deviated significantly from the neutral expectation in BE NCO, suggesting that factors related to H. pylori or H. pylori infection itself may influence EAC risk. Additionally, simulations incorporating selection recapitulated non-neutral behaviors observed in the datasets. Formally modeling dynamics during progression holds promise in clinical applications by offering a deeper understanding of microbial involvement in cancer development.

APOBEC3A deaminates CTG hairpin loops to promote fragility and instability of expanded CAG/CTG repeats

CAG/CTG repeats are prone to expansion, causing several inherited human diseases. The initiating sources of DNA damage which lead to inaccurate repair of the repeat tract to cause expansions are not fully understood. Expansion-prone CAG/CTG repeats are actively transcribed and prone to forming stable R-loops with hairpin structures forming on the displaced single-stranded DNA (S-loops). We previously determined that damage by the Saccharomyces cerevisiae cytosine deaminase, Fcy1, was required for both fragility and instability of CAG/CTG tracts engaged in R-loops. To determine whether this mechanism is more universal, we expressed human cytidine deaminases APOBEC3A (A3A), APOBEC3B (A3B), or activation-induced cytidine deaminase (AID) in our yeast system. We show that mutagenic activity of Apolipoprotein B messenger RNA-editing enzyme, catalytic polypeptides causes CAG/CTG fragility and instability, with A3A having the greatest effect followed by A3B and least from AID. A3A-induced repeat fragility was exacerbated by enrichment of R-loops at the repeat site. A3A and A3B-induced instability was dependent on the MutLγ nuclease and to a lesser extent, base excision repair factors. Deaminase activity assays on hairpin substrates containing CTG and GTC triplet sequences revealed that A3A prefers cytidines within the hairpin loop, and bulges in the hairpin stem alter preferred locations. Analysis of RNA expression levels in human cortex samples revealed that A3A is expressed in brain tissue that exhibits CAG/CTG repeat expansions and its expression is elevated in Huntington's disease (HD) patient samples. These results implicate cytidine deamination by A3A as a potential source of repeat expansions in HD and other CAG/CTG repeat expansion disorders.

Acral Melanoma: A Review of Its Pathogenesis, Progression, and Management

Acral melanoma is a distinct subtype of cutaneous malignant melanoma that uniquely occurs on ultraviolet (UV)-shielded, glabrous skin of the palms, soles, and nail beds. While acral melanoma only accounts for 2-3% of all melanomas, it represents the most common subtype among darker-skinned, non-Caucasian individuals. Unlike other cutaneous melanomas, acral melanoma does not arise from UV radiation exposure and is accordingly associated with a relatively low tumor mutational burden. Recent advances in genomic, transcriptomic, and epigenomic sequencing have revealed genetic alterations unique to acral melanoma, including novel driver genes, high copy number variations, and complex chromosomal rearrangements. This review synthesizes the current knowledge on the clinical features, epidemiology, and treatment approaches for acral melanoma, with a focus on the genetic pathogenesis that gives rise to its unique tumor landscape. These findings highlight a need to deepen our genetic and molecular understanding to better target this challenging subtype of melanoma.