Cancer genome landscapes

Omics-Enhanced Nanomedicine for Cancer Therapy

Cancer nanomedicine has emerged as a promising approach to overcome the limitations of conventional cancer therapies, offering enhanced efficacy and safety in cancer management. However, the inherent heterogeneity of tumors presents increasing challenges for the application of cancer nanomedicine in both diagnosis and treatment. This heterogeneity necessitates the integration of advanced and high-throughput analytical techniques to tailor nanomedicine strategies to individual tumor profiles. Omics technologies, encompassing genomics, epigenomics, transcriptomics, proteomics, metabolomics, and more, provide unparalleled insights into the molecular and cellular mechanisms underlying cancer. By dissecting tumor heterogeneity across multiple levels, these technologies offer robust support for the development of personalized and precise cancer nanomedicine strategies. In this review, the principles, techniques, and applications of key omics technologies are summarized. Especially, the synergistic integration of omics and nanomedicine in cancer therapy is explored, focusing on enhanced diagnostic accuracy, optimized therapeutic strategies and the assessment of nanomedicine-mediated biological responses. Moreover, this review addresses current challenges and outlines future directions in the field of omics-enhanced nanomedicine. By offering valuable insights and guidance, this review aims to advance the integration of omics with nanomedicine, ultimately driving improved diagnostic and therapeutic strategies for cancer.

Biological and genetic characterization of a newly established human primary multidrug-resistant distal cholangiocarcinoma cell line, CBC3T-6

Distal cholangiocarcinoma is a rare and highly aggressive malignant tumor. The inherent tumor characteristics and growth pattern of cancer cells pose a challenge for diagnosis and treatment. Chemotherapy resistance leads to limited treatment options for patients with advanced cholangiocarcinoma. However, drug resistance studies in cholangiocarcinoma are often limited by the use of preclinical models that do not accurately replicate the essential features of the disease. In this study, we established and characterized a primary multidrug-resistant distal cholangiocarcinoma cell line, CBC3T-6. STR profiling indicated no evidence of cross-contamination. This cell line remains stable during long-term in vitro culture and is characterized by short doubling times and rapid subcutaneous tumor formation in mice. In addition, among the first-line anticancer drugs for cholangiocarcinoma, CBC3T-6 cells showed varying degrees of resistance to gemcitabine, oxaliplatin, cisplatin, and 5-FU. Whole exome sequencing analysis revealed that CBC3T-6 cells contained a variety of potentially pathogenic somatic cell mutations, such as TP53 and KRAS mutations. ABCB1 mutation as a possible therapeutic target for multidrug resistance. In conclusion, CBC3T-6 cells can be used as a useful tool to study the mechanism of cholangiocarcinoma and develop new therapeutic strategies for multidrug resistance.

Upregulation of ABLIM1 Differentiates Intrahepatic Cholangiocarcinoma from Hepatocellular Carcinoma and Both Colorectal and Pancreatic Adenocarcinoma Liver Metastases

BACKGROUND

Altered gene expression in cancers holds great potential to improve the diagnostics and differentiation of primary and metastatic liver cancers. In this study, the expression of the protein-coding genes ring finger protein 135 (RNF135), ephrin-B2 (EFNB2), ring finger protein 125 (RNF125), homeobox-C 4 (HOXC4), actin-binding LIM protein 1 (ABLIM1) and oncostatin M receptor (OSMR) and the long non-coding RNAs (lncRNA) prospero homeobox 1 antisense RNA 1 (PROX1-AS1) and leukemia inhibitory factor receptor antisense RNA 1 (LIFR-AS1) was investigated in hepatocellular carcinoma, cholangiocarcinoma, colorectal liver metastases and pancreatic ductal adenocarcinoma liver metastases.

METHODS

This study included 149 formalin-fixed, paraffin-embedded samples from 80 patients. After RNA isolation, quantification, reverse transcription and preamplification, real-time qPCR was performed. The gene expression between different groups was calculated relative to the expression of the reference genes using the ∆∆Cq method and statistically analyzed. The expression of the genes was additionally analyzed using the AmiCA and UCSC Xena platforms.

RESULTS

In primary cancers, our results showed differential expression between primary tumors and healthy tissues for all the genes and lncRNA examined. Moreover, we found downregulation of RNF135 in hepatocellular carcinoma, downregulation of OSMR in colorectal liver metastases and upregulation of HOXC4 in cholangiocarcinoma compared to primary liver cancers and metastatic cancers. The major finding is the upregulation of ABLIM1 in cholangiocarcinoma compared to hepatocellular carcinoma, colorectal liver metastases, pancreatic ductal adenocarcinoma liver metastases and healthy liver tissue. We propose ABLIM1 as a potential biomarker that differentiates cholangiocarcinoma from other cancers and healthy liver tissue.

CONCLUSIONS

This study emphasizes the importance of understanding the differences in gene expression between healthy tissues and primary and metastatic cancers and highlights the potential use of altered gene expression as a diagnostic biomarker in these malignancies.

Multi-omics characterization and machine learning of lung adenocarcinoma molecular subtypes to guide precise chemotherapy and immunotherapy

Background

Lung adenocarcinoma (LUAD) is a heterogeneous tumor characterized by diverse genetic and molecular alterations. Developing a multi-omics-based classification system for LUAD is urgently needed to advance biological understanding.

Methods

Data on clinical and pathological characteristics, genetic alterations, DNA methylation patterns, and the expression of mRNA, lncRNA, and microRNA, along with somatic mutations in LUAD patients, were gathered from the TCGA and GEO datasets. A computational workflow was utilized to merge multi-omics data from LUAD patients through 10 clustering techniques, which were paired with 10 machine learning methods to pinpoint detailed molecular subgroups and refine a prognostic risk model. The disparities in somatic mutations, copy number alterations, and immune cell infiltration between high- and low-risk groups were assessed. The effectiveness of immunotherapy in patients was evaluated through the TIDE and SubMap algorithms, supplemented by data from various immunotherapy groups. Furthermore, the Cancer Therapeutics Response Portal (CTRP) and the PRISM Repurposing dataset (PRISM) were employed to investigate new drug treatment approaches for LUAD. In the end, the role of SLC2A1 in tumor dynamics was examined using RT-PCR, immunohistochemistry, CCK-8, wound healing, and transwell tests.

Results

By employing multi-omics clustering, we discovered two unique cancer subtypes (CSs) linked to prognosis, with CS2 demonstrating a better outcome. A strong model made up of 17 genes was created using a random survival forest (RSF) method, which turned out to be an independent predictor of overall survival and showed reliable and impressive performance. The low-risk group not only had a better prognosis but also was more likely to display the "cold tumor" phenotype. On the other hand, individuals in the high-risk group showed a worse outlook and were more likely to respond positively to immunotherapy and six particular chemotherapy medications. Laboratory cell tests demonstrated that SLC2A1 is abundantly present in LUAD tissues and cells, greatly enhancing the proliferation and movement of LUAD cells.

Conclusions

Thorough examination of multi-omics data offers vital understanding and improves the molecular categorization of LUAD. Utilizing a powerful machine learning system, we highlight the immense potential of the riskscore in providing individualized risk evaluations and customized treatment suggestions for LUAD patients.

Evaluation of Heterogeneity in the Coding Region of BRAF, MAP2K1, and MAP2K2 Genes in Primary and Metastatic Melanomas

INTRODUCTION

The incidence of melanoma has been increasing in recent decades. BRAF mutations appear in 50%-70% of melanomas. The BRAF-targeted therapy increased the disease-free survival of patients with metastatic melanoma, but this response may be short, due to several resistance mechanisms, such as the presence of other subclones with mutations. Evaluation of mutations and heterogeneity in the coding region of the BRAF, MAP2K1, and MAP2K2 genes in primary and metastatic melanomas.

PATIENTS AND METHODS

Twenty-seven samples of primary and metastatic superficial spreading melanoma (SSM) and acral lentiginous melanoma (ALM) were analyzed for BRAF, MAP2K1, and MAP2K2 mutations using the next-generation sequencing technique.

RESULTS

In ALM, the mutation rate found was 50% in the BRAF and MAP2K1 genes and 28.6% in MAP2K2. In the SSM, BRAF was mutated in 76.9%, MAP2K1 in 30.8%, and MAP2K2 in 23.2% of the cases. All samples were formed by distinct tumor subclones in the same lesion. Intertumoral heterogeneity was present between primary and metastatic lesions of ALM in BRAF, MAP2K1, and MAP2K2; the cases of SSM were heterogeneous for BRAF and MAP2K1.

CONCLUSION

We sought to evaluate the mutations in the BRAF, MAP2K1, and MAP2K2 genes, revealing a heterogeneous mutation profile in samples of ALM and SSM.

Protein structural context of cancer mutations reveals molecular mechanisms and candidate driver genes

Advances in protein structure determination and modeling allow us to study the structural context of human genetic variants on an unprecedented scale. Here, we analyze millions of cancer-associated missense mutations based on their structural locations and predicted perturbative effects. By considering the collective properties of mutations at the level of individual proteins, we identify distinct patterns associated with tumor suppressors and oncogenes. Tumor suppressors are enriched in structurally damaging mutations, consistent with loss-of-function mechanisms, while oncogene mutations tend to be structurally mild, reflecting selection for gain-of-function driver mutations and against loss-of-function mutations. Although oncogenes are difficult to distinguish from genes with no role in cancer using only structural damage, we find that the three-dimensional clustering of mutations is highly predictive. These observations allow us to identify candidate driver genes and speculate about their molecular roles, which we expect will have general utility in the analysis of cancer sequencing data.

Co-occurring mutations identify prognostic subgroups of microsatellite stable colorectal cancer

BACKGROUND

Co-occurring mutations in pairs of genes can pinpoint clinically relevant subgroups of cancer. Most colorectal cancers (CRCs) are microsatellite stable (MSS) and have few frequent mutations. Large patient cohorts and broad genomic coverage are needed for comprehensive co-mutation profiling.

METHODS

Co-mutations were identified in a population-based Swedish cohort analyzed by whole-genome sequencing (n=819 stage I-IV MSS CRCs). Prognostic value was further evaluated in a publicly available dataset of clinically sequenced metastatic CRCs (MSK-IMPACT; n=934 MSS). Multivariable Cox proportional hazards analyses with clinicopathological parameters were performed for locoregional (stage I-III) and metastatic (stage IV and recurrent) cancers separately.

RESULTS

Prevalent co-mutations were detected in 23 unique gene pairs, 20 of which included APC, TP53, KRAS and/or PIK3CA. Several co-mutations involving APC were associated with good overall survival in locoregional CRC, including APC-TCF7L2 (multivariable HR: 0.49, 95% CI 0.27-0.89). This co-mutation was prognostic also in metastatic cancers (multivariable HR: 0.49 and 0.37, 95% CI: 0.24-0.98 and 0.17-0.82 in the Swedish and MSK cohorts, respectively). APC-SOX9 co-mutations were mutually exclusive with APC-TCF7L2, and the co-mutations combined had stronger prognostic associations than APC alone in both metastatic cohorts. BRAF p.V600E-RNF43 co-mutations were associated with poor overall and recurrence-free survival in locoregional CRC (multivariable HR: 4.13 and 3.2, 95% CI: 1.78-9.54 and 1.53-8.04, respectively).

CONCLUSIONS

We report a genome-wide evaluation of co-occurring mutations in MSS CRCs, and suggest that co-mutations can improve the prognostic stratification compared to single mutations alone.

Integrative Computational Framework, Dyscovr, Links Mutated Driver Genes to Expression Dysregulation Across 19 Cancer Types

Though somatic mutations play a critical role in driving cancer initiation and progression, the systems-level functional impacts of these mutations-particularly, how they alter expression across the genome and give rise to cancer hallmarks-are not yet well-understood, even for well-studied cancer driver genes. To address this, we designed an integrative machine learning model, Dyscovr, that leverages mutation, gene expression, copy number alteration (CNA), methylation, and clinical data to uncover putative relationships between nonsynonymous mutations in key cancer driver genes and transcriptional changes across the genome. We applied Dyscovr pan-cancer and within 19 individual cancer types, finding both broadly relevant and cancer type-specific links between driver genes and putative targets, including a subset we further identify as exhibiting negative genetic relationships. Our work newly implicates-and validates in cell lines-KBTBD2 and mutant PIK3CA as putative synthetic lethals in breast cancer, suggesting a novel combinatorial treatment approach.

Integrated molecular and functional characterization of the intrinsic apoptotic machinery identifies therapeutic vulnerabilities in glioma

Genomic profiling often fails to predict therapeutic outcomes in cancer. This failure is, in part, due to a myriad of genetic alterations and the plasticity of cancer signaling networks. Functional profiling, which ascertains signaling dynamics, is an alternative method to anticipate drug responses. It is unclear whether integrating genomic and functional features of solid tumours can provide unique insight into therapeutic vulnerabilities. We perform combined molecular and functional characterization, via BH3 profiling of the intrinsic apoptotic machinery, in glioma patient samples and derivative models. We identify that standard-of-care therapy rapidly rewires apoptotic signaling in a genotype-specific manner, revealing targetable apoptotic vulnerabilities in gliomas containing specific molecular features (e.g., TP53 WT). However, integration of BH3 profiling reveals high mitochondrial priming is also required to induce glioma apoptosis. Accordingly, a machine-learning approach identifies a composite molecular and functional signature that best predicts responses of diverse intracranial glioma models to standard-of-care therapies combined with ABBV-155, a clinical drug targeting intrinsic apoptosis. This work demonstrates how complementary functional and molecular data can robustly predict therapy-induced cell death.

Therapeutic advances in the targeting of ROR1 in hematological cancers

Receptor tyrosine kinases (RTKs) are key cell surface receptors involved in cell communication and signal transduction, with great importance in cell growth, differentiation, survival, and metabolism. Dysregulation of RTKs, such as EGFR, VEGFR, HER2 or ROR, could lead to various diseases, particularly cancers. ROR1 has emerged as a promising target in hematological malignancies. The development of ROR1 targeted therapies is continuously growing leading to remarkable novel therapeutical approaches using mAbs, antibody-drug conjugates, several small molecules or CAR T cells which have shown encouraging preclinical results. In the hematological field, mAbs, small molecules, BiTEs or CAR T cell therapies displayed promising outcomes with the clinical trials data encouraging the use of anti-ROR1 therapies. This paper aims to offer a comprehensive analysis of the current landscape of ROR1-targeted therapies in hematological malignancies marking the innovative approaches with promising preclinical and clinical. Offering a better understanding of structural and functional aspects of ROR1 could lead to new perspectives in targeting a wide spectrum of malignancies.

Emerging Gene-editing nano-therapeutics for Cancer

Remarkable progress has been made in the field of genome engineering after the discovery of CRISPR/Cas9 in 2012 by Jennifer Doudna and Emmanuelle Charpentier. Compared to any other gene-editing tools, CRISPR/Cas9 attracted the attention of the scientific community because of its simplicity, specificity, and multiplex editing possibilities for which the inventors were awarded the Nobel prize for chemistry in 2020. CRISPR/Cas9 allows targeted alteration of the genomic sequence, gene regulation, and epigenetic modifications using an RNA-guided site-specific endonuclease. Though the impact of CRISPR/Cas9 was undisputed, some of its limitations led to key modifications including the use of miniature-Cas proteins, Cas9 Retron precise Parallel Editing via homologY (CRISPEY), Cas-Clover, or development of alternative methods including retron-recombineering, Obligate Mobile Element Guided Activity(OMEGA), Fanzor, and Argonaute proteins. As cancer is caused by genetic and epigenetic alterations, gene-editing was found to be highly useful for knocking out oncogenes, editing mutations to regain the normal functioning of tumor suppressor genes, knock-out immune checkpoint blockade in CAR-T cells, producing 'off-the-shelf' CAR-T cells, identify novel tumorigenic genes and functional analysis of multiple pathways in cancer, etc. Advancements in nanoparticle-based delivery of guide-RNA and Cas9 complex to the human body further enhanced the potential of CRISPR/Cas9 for clinical translation. Several studies are reported for developing novel delivery methods to enhance the tumor-specific application of CRISPR/Cas9 for anticancer therapy. In this review, we discuss new developments in novel gene editing techniques and recent progress in nanoparticle-based CRISPR/Cas9 delivery specific to cancer applications.

Whole-exome sequencing reveals novel genomic signatures and potential therapeutic targets during the progression of rectal neuroendocrine neoplasm

Rectal neuroendocrine neoplasms (rNENs) are among the most frequent gastrointestinal neuroendocrine neoplasms and pose a serious challenge for clinical management. The size of the primary neoplasm is considered to be the most important predictor of disease progression, but the genetic alterations that occur during the progression of rNENs remain unknown. Here, we performed a comprehensive whole-exome sequencing study on 54 tumor-normal paired, formalin-fixed paraffin-embedded specimens from patients locally diagnosed with rNENs. Of these, 81.5% (n = 44) were classified as small-sized (≤2 cm) rNENs, while the remainder (18.5%, n = 10) were classified as large-sized (>2 cm) rNEN samples. Comparative analysis revealed marked disparities in the mutational landscape between small- and large-sized rNEN samples, and between large-sized rNEN samples with or without lymph node metastases. The high-confidence driver genes RHPN2, MUC16, and MUC4 were significantly mutated in both small- and large-sized rNEN specimens, whereas mutations in MAN2A1, and BAG2 were only identified in large-sized specimens diagnosed with lymph node metastases. Correspondingly, we observed that the mTOR and MAPK pathways were preferentially enriched in the large-sized rNEN specimens. Signature-based analysis revealed that mutational processes associated with defective DNA base excision repair (SBS30) significantly accumulated in large-sized rNEN samples with lymph node metastases, highlighting the important role of this mutagenic process in promoting rNEN progression. We further found that most rNEN subjects, regardless of tumor size, harbored at least one alteration with targeted therapeutic implications. Taken together, these results elucidate the genetic features associated with tumor size and lymphatic metastasis in rNEN patients, which will deepen our understanding of the genetic changes during rNEN progression and potentially directing improvements in rNEN treatment strategies.

Cellular mechanisms of combining innate immunity activation with PD-1/PD-L1 blockade in treatment of colorectal cancer

PD-1/PD-L1 blockade therapies have displayed extraordinary clinical efficacy for melanoma, renal, bladder and lung cancer; however, only a minority of colorectal cancer (CRC) patients benefit from these treatments. The efficacy of PD-1/PD-L1 blockade in CRC is limited by the complexities of tumor microenvironment. PD-1/PD-L1 blockade immunotherapy is based on T cell-centered view of tumor immunity. However, the onset and maintenance of T cell responses and the development of long-lasting memory T cells depend on innate immune responses. Acknowledging the pivotal role of innate immunity in anti-tumor immune response, this review encapsulates the employment of combinational therapies those involve PD-1/PD-L1 blockade alongside the activation of innate immunity and explores the underlying cellular mechanisms, aiming to harnessing innate immune responses to induce long-lasting tumor control for CRC patients who received PD-1/PD-L1 blockade therapy.

Variability in non-tumor areas of colorectal cancer patients as revealed by endoscopic intestinal step biopsies

A comprehensive endoscopic small and large intestinal untargeted step biopsy procedure was conducted to compare gene expression between the normal intestinal mucosa of healthy individuals and that of patients with colorectal tumors. From 78 participants (healthy individuals [n = 17], patients with colorectal conventional adenomas [n = 6], patients with Tis-T1 colorectal cancer [n = 41], patients with T2-4 colorectal cancer [n = 14]), biopsies of normal mucosa of the terminal ileum, right-sided colon (cecum and ascending colon), and left-sided colorectum (descending colon, sigmoid colon, and rectum) were obtained using a lower gastrointestinal endoscope. RNA was extracted from all samples, and total transcriptome sequencing was performed. Transcriptome data from 388 samples was analyzed. DNA was also extracted from tumor biopsy tissues and analyzed for whole-exome sequencing. In healthy individuals, gene expression differed significantly among the terminal ileum, right-sided colon, and left-sided colorectum, presumably linked to embryological factors. There were differences in gene expression in the normal mucosa in colorectal cancer patients, compared to healthy controls. Patients with tumors, especially T2-4 colorectal cancer, showed considerable variation in gene expression in non-tumor tissues, even in the terminal ileum distant from the tumor site. Based on endoscopic biopsies, the results imply cancer-predisposing conditions in seemingly normal tissues. The present study points to the importance of small intestine and cancer-predisposing conditions in the colon of colorectal cancer patients, with possible implications for developing novel immunotherapy and other therapeutic modalities.

The Evolving Molecular Landscape and Actionable Alterations in Urologic Cancers

The genetic landscape of urologic cancers has evolved with the identification of actionable mutations that impact diagnosis, prognosis, and therapeutic strategies. This narrative review consolidates existing literature on genetic mutations across key urologic cancers, including bladder, renal, prostate, upper tract urothelial, testicular, and penile. The review highlights mutations in DNA damage repair genes, such as BRCA1/2 and PTEN, as well as pathway alterations like FGFR and PD-L1 overexpression. These mutations influence tumor behavior and therapeutic outcomes, emphasizing the need for precision oncology approaches. Molecular profiling, through tools like next-generation sequencing, has revolutionized patient care by enabling targeted treatment strategies, especially in cancers with distinct molecular subtypes such as luminal or basal bladder cancer and clear cell renal carcinoma. Emerging therapies, including FGFR inhibitors and immune checkpoint blockade, offer new treatment avenues, although resistance mechanisms remain a challenge. We also emphasize the importance of biomarker identification for personalized management, especially in metastatic settings where treatment intensification is often required. Future research is needed to further elucidate our understanding of the genetics affecting urologic cancers, which will help develop novel, individualized therapies to enhance oncologic outcomes.

Molecular Characterization and Classification of HER2-Positive Breast Cancer Inform Tailored Therapeutic Strategies

HER2-positive breast cancer is an aggressive subtype that accounts for 15% to 20% of all breast cancers. Recent studies have suggested that HER2-positive breast cancer is a group of heterogeneous diseases with different sensitivities to standard treatment regimens. Revealing the molecular heterogeneity of HER2-positive breast cancer could potentially enable more precise treatment strategies. In this study, we performed multiomics profiling on a HER2-positive breast cancer cohort and identified four transcriptome-based subtypes. The classical HER2 (HER2-CLA) subtype comprised 28.3% of the samples and displayed high ERBB2 activation and significant benefit from anti-HER2 therapy. The immunomodulatory (HER2-IM) subtype (20%) featured an immune-activated microenvironment, potentially suitable for de-escalated treatment and immunotherapy. The luminal-like (HER2-LUM) subtype (30.6%) possessed similar molecular features of hormone receptor-positive HER2-negative breast cancer, suggesting endocrine therapy and CDK4/6 inhibitors as a potential therapeutic strategy. Lastly, the basal/mesenchymal-like (HER2-BM) subtype (21.1%) had a poor response to current dual HER2-targeted therapy and could potentially benefit from tyrosine kinase inhibitors. The molecular characteristics and clinical features of the subtypes were further explored across multiple cohorts, and the feasibility of the proposed treatment strategies was validated in patient-derived organoid and patient-derived tumor fragment models. This study elucidates the molecular heterogeneity of HER2-positive breast cancer and paves the way for a more tailored treatment. Significance: Illumination of the inherent heterogeneity within HER2-positive breast cancers through the delineation of distinct molecular subtypes lays the groundwork for developing more personalized treatment strategies based on specific patient characteristics.

Leveraging the Photofunctions of Transition Metal Complexes for the Design of Innovative Phototherapeutics

Despite the advent of various medical interventions for cancer treatment, the disease continues to pose a formidable global health challenge, necessitating the development of new therapeutic approaches for more effective treatment outcomes. Photodynamic therapy (PDT), which utilizes light to activate a photosensitizer to produce cytotoxic reactive oxygen species (ROS) for eradicating cancer cells, has emerged as a promising approach for cancer treatment due to its high spatiotemporal precision and minimal invasiveness. However, the widespread clinical use of PDT faces several challenges, including the inefficient production of ROS in the hypoxic tumor microenvironment, the limited penetration depth of light in biological tissues, and the inadequate accumulation of photosensitizers at the tumor site. Over the past decade, there has been increasing interest in the utilization of photofunctional transition metal complexes as photosensitizers for PDT applications due to their intriguing photophysical and photochemical properties. This review provides an overview of the current design strategies used in the development of transition metal complexes as innovative phototherapeutics, aiming to address the limitations associated with PDT and achieve more effective treatment outcomes. The current challenges and future perspectives on the clinical translation of transition metal complexes are also discussed.

Exosomal miR-155-5p promote the occurrence of carotid atherosclerosis

Periodontitis is a significant independent risk factor for atherosclerosis. Yet, the exact mechanism of action is still not fully understood. In this study, we investigated the effect of exosomes-miR-155-5p derived from periodontal endothelial cells on atherosclerosis in vitro and in vivo. Higher expression of miR-155-5p was detected in the plasma exosomes of patients with chronic periodontitis (CP) and carotid atherosclerosis (CAS) compared to patients with CP. Also, the expression level of miR-155-5p was associated with the severity of CP. miR-155-5p-enriched exosomes from HUVECs increased the angiogenesis and permeability of HAECs and promoted the expression of angiogenesis, permeability, and inflammation genes. Along with the overexpression or inhibition of miR-155-5p, the biological effect of HUVECs-derived exosomes on HAECs changed correspondingly. In ApoE-/- mouse models, miR-155-5p-enriched exosomes promoted the occurrence of carotid atherosclerosis by increasing permeable and angiogenic activity. Collectively, these findings highlight a molecular mechanism of periodontitis in CAS, uncovering exosomal miR-155-5p derived periodontitis affecting carotid endothelial cells in an 'exosomecrine' manner. Exosomal miR-155-5p may be used as a biomarker and target for clinical intervention to control this intractable disease in future, and the graphic abstract was shown in Figure S1.

Serum DNA methylome of the colorectal cancer serrated pathway enables non-invasive detection

The clinical relevance of the colorectal cancer serrated pathway is evident, but the screening of serrated lesions remains challenging. We aimed to characterize the serum methylome of the serrated pathway and to evaluate circulating cell-free DNA (cfDNA) methylomes as a potential source of biomarkers for the non-invasive detection of serrated lesions. We collected serum samples from individuals with serrated adenocarcinoma (SAC), traditional serrated adenomas, sessile serrated lesions, hyperplastic polyps and individuals with no colorectal findings. First, we quantified cfDNA methylation with the MethylationEPIC array. Then, we compared the methylation profiles with tissue and serum datasets. Finally, we evaluated the utility of serum cfDNA methylation biomarkers. We identified a differential methylation profile able to distinguish high-risk serrated lesions from no serrated neoplasia, showing concordance with tissue methylation from SAC and sessile serrated lesions. Serum methylation profiles are pathway-specific, clearly separating serrated lesions from conventional adenomas. The combination of ninjurin 2 (NINJ2) and glutamate-rich 1 (ERICH1) methylation discriminated high-risk serrated lesions and SAC with 91.4% sensitivity (64.4% specificity), while zinc finger protein 718 (ZNF718) methylation reported 100% sensitivity for the detection of SAC (96% specificity). This is the first study exploring the serum methylome of serrated lesions. Differential methylation of cfDNA can be used for the non-invasive detection of colorectal serrated lesions.

Mutational landscape induced by chronic exposure to environmental PM10 and PM2.5 in A549 lung epithelial cell

Exposure to particulate matter (PM) has been linked to an increased risk of multiple diseases, primarily lung cancer, through various molecular mechanisms. However, the mutagenic potential of PM remains unclear. This study aimed to provide a comprehensive description of genetic mutations and mutagenic signatures resulting from chronic exposure to PM10 or PM2.5. Using whole exome sequencing, we identified driver mutations and mutational signatures in A549 cells, a lung epithelial cell model subjected to weekly exposure to either PM10 or PM2.5, for a period of 28 weeks. The number of single nucleotide variations, insertions, and deletions increased depending on the duration of exposure. PM10 generated the highest number of genomic alterations. Amplifications in SYK (oncogene) and mutations in NCOR1 (tumor suppressor gene) were prevalent in cells exposed to either PM10 or PM2.5; however, other mutations were exclusive, such as TP53 and ANK3 for PM10, and ERCC1 and ERCC2 for PM2.5. Different p53-related signaling pathways were most enriched by driver mutations upon exposure to both PM10 and PM2.5, particularly the glucose deprivation pathway. Exposure to either PM10 or PM2.5 resulted in high frequencies of C > A substitutions and one-base insertions/deletions in microhomology sites. The single-base substitution (SBS) signature SBS05, related to the nucleotide excision DNA repair pathway, contributed the most to both PM10-and PM2.5-exposed cells. The contribution of signature SBS18, related to oxidative stress, was observed in cells exposed to either PM10 or PM2.5, but a greater contribution was observed in PM2.5-exposed cells. In addition, SBS03 and SBS36, which are related to different DNA damage repair mechanisms, were observed more frequently in PM10-exposed cells. We assessed the mutagenic potential of PM10 and PM2.5, as a complete mixture, identifying mutated driver genes and mutational signatures generated by chronic PM exposure, which could contribute to the development of cancer, cardiovascular, and digestive diseases.

DNMT3AR882H Is Not Required for Disease Maintenance in Primary Human AML, but Is Associated With Increased Leukemia Stem Cell Frequency

Genetic mutations are being thoroughly mapped in human cancers, yet a fundamental question in cancer biology is whether such mutations are functionally required for cancer initiation, maintenance of established cancer, or both. Here, we study this question in the context of human acute myeloid leukemia (AML), where DNMT3A R882 missense mutations often arise early, in pre-leukemic clonal hematopoiesis, and corrupt the DNA methylation landscape to initiate leukemia. We developed CRISPR-based methods to directly correct DNMT3A R882 mutations in leukemic cells obtained from patients. Surprisingly, DNMT3A R882 mutations were largely dispensable for disease maintenance. Replacing DNMT3A R882 mutants with wild-type DNMT3A did not impair the ability of AML cells to engraft in vivo, and minimally altered DNA methylation. Taken together, DNMT3A R882 mutations are initially necessary for AML initiation, but are largely dispensable for disease maintenance. The notion that initiating oncogenes differ from those that maintain cancer has important implications for cancer evolution and therapy.

Accumulation of Oncogenic Mutations During Progression from Healthy Tissue to Cancer

Cancers are typically fueled by sequential accumulation of driver mutations in a previously healthy cell. Some of these mutations, such as inactivation of the first copy of a tumor suppressor gene, can be neutral, and some, like those resulting in activation of oncogenes, may provide cells with a selective growth advantage. We study a multi-type branching process that starts with healthy tissue in homeostasis and models accumulation of neutral and advantageous mutations on the way to cancer. We provide results regarding the sizes of premalignant populations and the waiting times to the first cell with a particular combination of mutations, including the waiting time to malignancy. Finally, we apply our results to two specific biological settings: initiation of colorectal cancer and age incidence of chronic myeloid leukemia. Our model allows for any order of neutral and advantageous mutations and can be applied to other evolutionary settings.

Evolution of Molecular Biomarkers and Precision Molecular Therapeutic Strategies in Glioblastoma

Glioblastoma is the most commonly occurring malignant brain tumor, with a high mortality rate despite current treatments. Its classification has evolved over the years to include not only histopathological features but also molecular findings. Given the heterogeneity of glioblastoma, molecular biomarkers for diagnosis have become essential for initiating treatment with current therapies, while new technologies for detecting specific variations using computational tools are being rapidly developed. Advances in molecular genetics have made possible the creation of tailored therapies based on specific molecular targets, with various degrees of success. This review provides an overview of the latest advances in the fields of histopathology and radiogenomics and the use of molecular markers for management of glioblastoma, as well as the development of new therapies targeting the most common molecular markers. Furthermore, we offer a summary of the results of recent preclinical and clinical trials to recognize the current trends of investigation and understand the possible future directions of molecular targeted therapies in glioblastoma.

A method for in silico exploration of potential glioblastoma multiforme attractors using single-cell RNA sequencing

We presented a method to find potential cancer attractors using single-cell RNA sequencing (scRNA-seq) data. We tested our method in a Glioblastoma Multiforme (GBM) dataset, an aggressive brain tumor presenting high heterogeneity. Using the cancer attractor concept, we argued that the GBM's underlying dynamics could partially explain the observed heterogeneity, with the dataset covering a representative region around the attractor. Exploratory data analysis revealed promising GBM's cellular clusters within a 3-dimensional marker space. We approximated the clusters' centroid as stable states and each cluster covariance matrix as defining confidence regions. To investigate the presence of attractors inside the confidence regions, we constructed a GBM gene regulatory network, defined a model for the dynamics, and prepared a framework for parameter estimation. An exploration of hyperparameter space allowed us to sample time series intending to simulate myriad variations of the tumor microenvironment. We obtained different densities of stable states across gene expression space and parameters displaying multistability across different clusters. Although we used our methodological approach in studying GBM, we would like to highlight its generality to other types of cancer. Therefore, this report contributes to an advance in the simulation of cancer dynamics and opens avenues to investigate potential therapeutic targets.

Senescence Reprogramming by MTHFD2 Deficiency Facilitates Tumor Progression

Background: Age is a critical risk factor for cancer, as its incidence and mortality increase with age. However, there is limited understanding of the molecular changes aging induces in tumors. Methods: We explored demographic differences between young and old cancer patients and identified age sixty and above as pivotal in cancer prognosis. Subsequently, we developed an aging-related prognostic model based on genes to assess senescence's impact on aging-associated cancer. Grounded in the coefficients and expression levels of these identified signature genes, a risk score was computed, enabling the classification of collected samples into aging-related high-risk and low-risk cohorts. Results: Our study revealed increased genomic instability and somatic mutations in tumors from older individuals. We also found alterations in carcinogenic signaling pathways, particularly immune responses, inflammatory pathways, and cell cycle arrest in susceptible populations. Single-cell RNA sequencing showed heightened frequencies of exhausted T cells, myeloid cells, and B cells in high-risk cohorts. Conclusion: MTHFD2 emerged as a crucial molecular switch regulating senescence in cancer. Its deletion promoted tumor growth by inducing cell senescence and stimulating the senescence-associated secretory phenotype (SASP) in senescent tumor cells. This highlights the need for tailored methodologies in effective cancer management.

Bioinformatic and experimental analyses of GATA3 and its regulatory miRNAs in breast Cancer

BACKGROUND

GATA binding protein 3 (GATA3) is a transcription factor that plays a critical role in the differentiation and function of luminal epithelial cells in the breast. MicroRNAs (miRNAs) are small non-coding RNAs that modulate gene expression and their dysregulation has been implicated in cancer. The purpose of this study was to investigate the expression of GATA3 and its corresponding targeting miRNAs in breast cancer.

MATERIALS AND METHODS

In this study, we used bioinformatic tools, including the miRWalk database and RNA Hybrid online tool, to identify potential miRNAs that target the GATA3 mRNA. Then, we collected frozen tissue specimens from 67 breast cancer patients and 67 adjacent normal breast tissue samples and evaluated the expression levels of GATA3, hsa-miR-433-3p, and hsa-miR-144-3p using quantitative RT-PCR.

RESULTS

We found that hsa-miR-433-3p and hsa-miR-144-3p are potential miRNAs that target the GATA3 mRNA, and we found that both were significantly downregulated in breast cancer tissues relative to adjacent normal breast tissues (P < 0.0001). We also observed a significant upregulation of the GATA3 mRNA in breast cancer tissues (P < 0.0001). Additionally, we found that their dysregulation was associated with clinicopathological features such as invasive carcinoma and carcinoma in situ subtypes, tumor grade, estrogen receptor status, progesterone receptor status, and HER2 status.

CONCLUSIONS

Our study represents the first attempt to investigate the expression of GATA3 and its targeting miRNAs simultaneously in breast cancer. Our findings suggest that dysregulation of these genes may contribute to breast cancer development and progression.

Targeting Protein Kinase, Membrane-Associated Tyrosine/Threonine 1 (PKMYT1) for Precision Cancer Therapy: From Discovery to Clinical Trial

\Protein kinase membrane-associated tyrosine/threonine 1 (PKMYT1), an overlooked member of the WEE family responsible for regulating cell cycle transition, has recently emerged as a compelling therapeutic target for precision cancer therapy due to its established synthetic lethal relationship with CCNE1 (cyclin E1) amplification. Since the first-in-class selective PKMYT1 inhibitor, RP-6306, entered clinical trials in 2021, the field has experienced renewed interest underscored by the growing number of inhibitor patents and the exploration of additional gene alterations, such as KRAS/p53 mutations, FBXW7 mutation, and PPP2R1A mutation, as novel synthetic lethal partners. This perspective summarizes, for the first time, the PKMYT1 structure, function, and inhibitors in both the literature and patent applications reported to date. Compounds are described focusing on their design and optimization process, structural features, and biological activity with the aim to promoting further drug discovery efforts targeting PKMYT1 as a potential precision therapy.

Spatiotemporal lineage tracing reveals the dynamic spatial architecture of tumor growth and metastasis

Tumor progression is driven by dynamic interactions between cancer cells and their surrounding microenvironment. Investigating the spatiotemporal evolution of tumors can provide crucial insights into how intrinsic changes within cancer cells and extrinsic alterations in the microenvironment cooperate to drive different stages of tumor progression. Here, we integrate high-resolution spatial transcriptomics and evolving lineage tracing technologies to elucidate how tumor expansion, plasticity, and metastasis co-evolve with microenvironmental remodeling in a Kras;p53-driven mouse model of lung adenocarcinoma. We find that rapid tumor expansion contributes to a hypoxic, immunosuppressive, and fibrotic microenvironment that is associated with the emergence of pro-metastatic cancer cell states. Furthermore, metastases arise from spatially-confined subclones of primary tumors and remodel the distant metastatic niche into a fibrotic, collagen-rich microenvironment. Together, we present a comprehensive dataset integrating spatial assays and lineage tracing to elucidate how sequential changes in cancer cell state and microenvironmental structures cooperate to promote tumor progression.

Deletions Rate-Limit Breast and Ovarian Cancer Initiation

Optimizing prevention and early detection of cancer requires understanding the number, types and timing of driver mutations. To quantify this, we exploited the elevated cancer incidence and mutation rates in germline BRCA1 and BRCA2 (gBRCA1/2) carriers. Using novel statistical models, we identify genomic deletions as the likely rate-limiting mutational processes, with 1-3 deletions required to initiate breast and ovarian tumors. gBRCA1/2-driven hereditary and sporadic tumors undergo convergent evolution to develop a similar set of driver deletions, and deletions explain the elevated cancer risk of gBRCA1/2-carriers. Orthogonal mutation timing analysis identifies deletions of chromosome 17 and 13q as early, recurrent events. Single-cell analyses confirmed deletion rate differences in gBRCA1/2 vs. non-carrier tumors as well as cells engineered to harbor gBRCA1/2. The centrality of deletion-associated chromosomal instability to tumorigenesis shapes interpretation of the somatic evolution of non-malignant tissue and guides strategies for precision prevention and early detection.

Targeting STAT3, FOXO3a, and Pim-1 kinase by FDA-approved tyrosine kinase inhibitor-Radotinib: An in silico and in vitro approach

Cancer, a multifactorial pathological condition, is primarily caused due to mutations in multiple genes. Hepatocellular carcinoma (HCC) is a form of primary liver cancer that is often diagnosed at the advanced stage. Current treatment strategies for advanced HCC involve systemic therapies which are often hindered due to the emergence of resistance and toxicity. Therefore, a multitarget approach might prove more effective in HCC treatment. The present study focuses on targeting signal transducer and activator of transcription 3 (STAT3), forkhead box class O3a (FOXO3a), and proviral integration site for Moloney murine leukemia virus-1 (Pim-1) kinase, using a Food and Drug Administration (FDA)-approved anticancer drug library. Two compounds, namely, radotinib and capmatinib, were identified as top compounds using molecular docking. Among the two compounds, radotinib exhibited significant binding values towards the targeted proteins and their heterodimers. Furthermore, in vitro experiments involving 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT), live/dead, 4',6-diamidino-2-phenylindole, and clonogenic assays were performed to evaluate the effect of radotinib in human hepatoblastoma cell line/hepatocellular carcinoma cells. The gene expression data indicated reduced expression of FOXO3a and Pim-1, but no basal-level alteration of STAT3. The Western blot analysis assay showed that the phosphorylation level of STAT3 was significantly decreased upon radotinib treatment. Taken together, our findings suggest that radotinib, which is currently used in the treatment of chronic myeloid leukemia (CML), could be considered as a potential candidate for repurposing in the treatment of HCC.

FTO/m6A mediates miR-138-5p maturation and regulates gefitinib resistance of lung adenocarcinoma cells by miR-138-5p/LCN2 axis

BACKGROUND

Lung cancer (LC) occupies an important position in the lethality of cancer patients. Acquired resistance to gefitinib in lung adenocarcinoma (LUAD) seriously affects the therapeutic efficacy of LC. Thus, it is of major scientific and clinical significance to probe the mechanism of gefitinib resistance in LUAD for ameliorating the prognosis of patients.

METHODS

The expression of miRNAs in gefitinib-resistant LUAD cells was validated using qRT-PCR. Cell viability was assessed through CCK-8, whereas cell death was examined through PI staining. Changes in the ferroptosis process were evaluated by detecting the intracellular Glutathione (GSH), Malondialdehyde (MDA), and Reactive Oxygen Species (ROS) levels. Downstream targets of miR-138-5p were verified via luciferase reporter and RNA pull-down assays. RIP and qRT-PCR were employed to evaluate pri-miR-138-5p binding to DiGeorge critical region 8 (DGCR8) and the pri-miR-138-5p m6A modification level. Additionally, the impact of fat mass and obesity-associated protein (FTO) on LUAD gefitinib sensitivity was assessed in vivo by constructing a xenograft model.

RESULTS

We observed that miR-138-5p was notably diminished in gefitinib-resistant cells. Overexpression of miR-138-5p suppressed viability while facilitated cell death and intracellular ferroptosis in gefitinib-resistant cells. Moreover, lipocalin 2 (LCN2) was the downstream target of miR-138-5p. The biological functions of miR-138-5p on gefitinib-resistant cells was reversed by introduction of LCN2. FTO suppressed the binding of DGCR8 to pri-miR-138-5p through m6A modification, thereby restraining the processing of miR-138-5p. Meanwhile, silencing of FTO enhanced the sensitivity of LUAD to gefitinib treatment.

CONCLUSION

FTO suppressed the processing of miR-138-5p and then modulated the proliferation, death, and ferroptosis of gefitinib-resistant cells through the miR-138-5p/LCN2 pathway, which may put forward novel insights for clinically ameliorating the therapeutic effect of gefitinib in LUAD.

ddPCR Overcomes the CRISPR-Cas13a-Based Technique for the Detection of the BRAF p.V600E Mutation in Liquid Biopsies

The isolation of circulating tumoral DNA (ctDNA) present in the bloodstream brings about the opportunity to detect genomic aberrations from the tumor of origin. However, the low amounts of ctDNA present in liquid biopsy samples makes the development of highly sensitive techniques necessary to detect targetable mutations for the diagnosis, prognosis, and monitoring of cancer patients. Here, we employ standard genomic DNA (gDNA) and eight liquid biopsy samples from different cancer patients to examine the newly described CRISPR-Cas13a-based technology in the detection of the BRAF p.V600E actionable point mutation and appraise its diagnostic capacity with two PCR-based techniques: quantitative Real-Time PCR (qPCR) and droplet digital PCR (ddPCR). Regardless of its lower specificity compared to the qPCR and ddPCR techniques, the CRISPR-Cas13a-guided complex was able to detect inputs as low as 10 pM. Even though the PCR-based techniques have similar target limits of detection (LoDs), only the ddPCR achieved a 0.1% variant allele frequency (VAF) detection with elevated reproducibility, thus standing out as the most powerful and suitable tool for clinical diagnosis purposes. Our results also demonstrate how the CRISPR-Cas13a can detect low amounts of the target of interest, but its base-pair specificity failed in the detection of actionable point mutations at a low VAF; therefore, the ddPCR is still the most powerful and suitable technique for these purposes.

Microarray analysis points to LMNB1 and JUN as potential target genes for predicting metastasis promotion by etoposide in colorectal cancer

Etoposide is a second-line chemotherapy agent widely used for metastatic colorectal cancer. However, we discovered that etoposide treatment induced greater motility potential in four colorectal cancer cell lines. Therefore, we used microarrays to test the mRNA of these cancer cell lines to investigate the mechanisms of etoposide promoting colorectal cancer metastasis. Differentially expressed genes (DEGs) were identified by comparing the gene expression profiles in samples from etoposide-treated cells and untreated cells in all four colorectal cancer cell lines. Next, these genes went through the Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway analysis. Among the top 10 genes including the upregulated and downregulated, eight genes had close interaction according to the STRING database: FAS, HMMR, JUN, LMNB1, MLL3, PLK2, STAG1 and TBL1X. After etoposide treatment, the cell cycle, metabolism-related and senescence signaling pathways in the colorectal cancer cell lines were significantly downregulated, whereas necroptosis and oncogene pathways were significantly upregulated. We suggest that the differentially expressed genes LMNB1 and JUN are potential targets for predicting colorectal cancer metastasis. These results provide clinical guidance in chemotherapy, and offer direction for further research in the mechanism of colorectal cancer metastasis.

Age at Tumor Diagnosis in 14,636 Canine Cases from the Pathology-Based UNIPI Animal Cancer Registry, Italy: One Size Doesn't Fit All

Cancer is the most common cause of death in adult dogs. All dogs would benefit from early diagnosis, but there are no specific guidelines regarding the schedule of cancer screening in companion animals. The aim of this study was to retrospectively evaluate the age at diagnosis in Italian oncological canine patients. A total of 14,636 canine histologically confirmed neoplastic cases were coded according to the Vet-ICD-O-canine-1 and stratified by malignancy, sex, neutering status, breed, cephalic index, body size, and tumor type. Differences in age distribution were analyzed and the influence of these variables on the time of first malignancy diagnosis was assessed using an event history analysis model. The median age at diagnosis for benign and malignant tumors was 9 and 10 years, respectively. Intact and purebred dogs were diagnosed earlier, but the median age differed significantly by breed. The earliest age at diagnosis was recorded for lymphomas and mast cell tumors. The model showed an accelerating effect of large size, brachy- and dolichocephaly, and sexual integrity in female dogs on the time of malignancy diagnosis. Our results confirm that a "one-size-fits-all" approach to cancer screening is not accurate in dogs and provide relevant data that may lead to the establishment of breed-based screening schedules.

Shedding light on the DICER1 mutational spectrum of uncertain significance in malignant neoplasms

The Dicer protein is an indispensable player in such fundamental cell pathways as miRNA biogenesis and regulation of protein expression in a cell. Most recently, both germline and somatic mutations in DICER1 have been identified in diverse types of cancers, which suggests Dicer mutations can lead to cancer progression. In addition to well-known hotspot mutations in RNAase III domains, DICER1 is characterized by a wide spectrum of variants in all the functional domains; most are of uncertain significance and unstated clinical effects. Moreover, various new somatic DICER1 mutations continuously appear in cancer genome sequencing. The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. Consequently, such analysis should be conducted based on the functional and structural characteristics of each protein, using a well-grounded targeted dataset rather than relying on large amounts of unsupervised data. Domains are the functional and evolutionary units of a protein; the analysis of the whole protein should be based on separate and independent examinations of each domain by their evolutionary reconstruction. Dicer represents a hallmark example of a multidomain protein, and we confirmed the phylogenetic multidomain approach being beneficial for the clinical effect prediction of Dicer variants. Because Dicer was suggested to have a putative role in hematological malignancies, we examined variants of DICER1 occurring outside the well-known hotspots of the RNase III domain in this type of cancer using phylogenetic reconstruction of individual domain history. Examined substitutions might disrupt the Dicer function, which was demonstrated by molecular dynamic simulation, where distinct structural alterations were observed for each mutation. Our approach can be utilized to study other multidomain proteins and to improve clinical effect evaluation.

Challenges and Outlooks in Precision Medicine: Expectations Versus Reality

Recent developments in technology have led to rapid advances in precision medicine, especially due to the rise of next-generation sequencing and molecular profiling. These technological advances have led to rapid advances in research, including increased tumor subtype resolution, new therapeutic agents, and mechanistic insights. Certain therapies have even been approved for molecular biomarkers across histopathological diagnoses; however, translation of research findings to the clinic still faces a number of challenges. In this review, the authors discuss several key challenges to the clinical integration of precision medicine, including the blood-brain barrier, both a lack and excess of molecular targets, and tumor heterogeneity/escape from therapy. They also highlight a few key efforts to address these challenges, including new frontiers in drug delivery, a rapidly expanding treatment repertoire, and improvements in active response monitoring. With continued improvements and developments, the authors anticipate that precision medicine will increasingly become the gold standard for clinical care.

Integrated diagnostics, complex biomarkers, and a new frontier for tissue pathology

What will be the next disruptive technology that will change pathology's routine practice again? In this editorial we make a case for the need of more complex biomarkers in oncology diagnostics, to match the inherent complexity of cancer biology. This complexity will be achieved by the validation of technology able to generate more meaningful biological datapoints (epitomized in tissue pathology by technologies such as multiplex immunofluorescence) and, more important, by the systematic analysis of multimodal technology outputs with artificial intelligence tools, which is the essence of integrated diagnostics. While describing these processes, the authors highlight the pivotal role that histopathology will play, once again, in yet another transformation in diagnostics.

Correcting for Observation Bias in Cancer Progression Modeling

Tumor progression is driven by the accumulation of genetic alterations, including both point mutations and copy number changes. Understanding the temporal sequence of these events is crucial for comprehending the disease but is not directly discernible from cross-sectional genomic data. Cancer progression models, including Mutual Hazard Networks (MHNs), aim to reconstruct the dynamics of tumor progression by learning the causal interactions between genetic events based on their co-occurrence patterns in cross-sectional data. Here, we highlight a commonly overlooked bias in cross-sectional datasets that can distort progression modeling. Tumors become clinically detectable when they cause symptoms or are identified through imaging or tests. Detection factors, such as size, inflammation (fever, fatigue), and elevated biochemical markers, are influenced by genomic alterations. Ignoring these effects leads to "conditioning on a collider" bias, where events making the tumor more observable appear anticorrelated, creating false suppressive effects or masking promoting effects among genetic events. We enhance MHNs by incorporating the effects of genetic progression events on the inclusion of a tumor in a dataset, thus correcting for collider bias. We derive an efficient tensor formula for the likelihood function and apply it to two datasets from the MSK-IMPACT study. In colon adenocarcinoma, we observe a significantly higher rate of clinical detection for TP53-positive tumors, while in lung adenocarcinoma, the same is true for EGFR-positive tumors. Compared to classical MHNs, this approach eliminates several spurious suppressive interactions and uncovers multiple promoting effects.

LineageVAE: reconstructing historical cell states and transcriptomes toward unobserved progenitors

MOTIVATION

Single-cell RNA sequencing (scRNA-seq) enables comprehensive characterization of the cell state. However, its destructive nature prohibits measuring gene expression changes during dynamic processes such as embryogenesis or cell state divergence due to injury or disease. Although recent studies integrating scRNA-seq with lineage tracing have provided clonal insights between progenitor and mature cells, challenges remain. Because of their experimental nature, observations are sparse, and cells observed in the early state are not the exact progenitors of cells observed at later time points. To overcome these limitations, we developed LineageVAE, a novel computational methodology that utilizes deep learning based on the property that cells sharing barcodes have identical progenitors.

RESULTS

LineageVAE is a deep generative model that transforms scRNA-seq observations with identical lineage barcodes into sequential trajectories toward a common progenitor in a latent cell state space. This method enables the reconstruction of unobservable cell state transitions, historical transcriptomes, and regulatory dynamics at a single-cell resolution. Applied to hematopoiesis and reprogrammed fibroblast datasets, LineageVAE demonstrated its ability to restore backward cell state transitions and infer progenitor heterogeneity and transcription factor activity along differentiation trajectories.

AVAILABILITY AND IMPLEMENTATION

The LineageVAE model was implemented in Python using the PyTorch deep learning library. The code is available on GitHub at https://github.com/LzrRacer/LineageVAE/.

Oncogenic Control of Metabolism

A cell committed to proliferation must reshape its metabolism to enable robust yet balanced production of building blocks for the assembly of proteins, lipids, nucleic acids, and other macromolecules, from which two functional daughter cells can be produced. The metabolic remodeling associated with proliferation is orchestrated by a number of pro-proliferative signaling nodes, which include phosphatidylinositol-3 kinase (PI3K), the RAS family of small GTPases, and transcription factor c-myc In metazoan cells, these signals are activated in a paracrine manner via growth factor-mediated activation of receptor (or receptor-associated) tyrosine kinases. Such stimuli are limited in duration and therefore allow the metabolism of target cells to return to the resting state once the proliferation demands have been satisfied. Cancer cells acquire activating genetic alterations within common pro-proliferative signaling nodes. These alterations lock cellular nutrient uptake and utilization into a perpetual progrowth state, leading to the aberrant accumulation and spread of cancer cells.

Early detection of pancreatic cancer in the era of precision medicine

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related mortality and it is often diagnosed at advanced stages due to non-specific clinical presentation. Disease detection at localized disease stage followed by surgical resection remains the only potentially curative treatment. In this era of precision medicine, a multifaceted approach to early detection of PDAC includes targeted screening in high-risk populations, serum biomarkers and "liquid biopsies", and artificial intelligence augmented tumor detection from radiologic examinations. In this review, we will review these emerging techniques in the early detection of PDAC.

Tumour mutational burden: clinical utility, challenges and emerging improvements

Tumour mutational burden (TMB), defined as the total number of somatic non-synonymous mutations present within the cancer genome, varies across and within cancer types. A first wave of retrospective and prospective research identified TMB as a predictive biomarker of response to immune-checkpoint inhibitors and culminated in the disease-agnostic approval of pembrolizumab for patients with TMB-high tumours based on data from the Keynote-158 trial. Although the applicability of outcomes from this trial to all cancer types and the optimal thresholds for TMB are yet to be ascertained, research into TMB is advancing along three principal avenues: enhancement of TMB assessments through rigorous quality control measures within the laboratory process, including the mitigation of confounding factors such as limited panel scope and low tumour purity; refinement of the traditional TMB framework through the incorporation of innovative concepts such as clonal, persistent or HLA-corrected TMB, tumour neoantigen load and mutational signatures; and integration of TMB with established and emerging biomarkers such as PD-L1 expression, microsatellite instability, immune gene expression profiles and the tumour immune contexture. Given its pivotal functions in both the pathogenesis of cancer and the ability of the immune system to recognize tumours, a profound comprehension of the foundational principles and the continued evolution of TMB are of paramount relevance for the field of oncology.

Mechanisms of Germline Stem Cell Competition across Species

In this review, we introduce the concept of cell competition, which occurs between heterogeneous neighboring cell populations. Cells with higher relative fitness become "winners" that outcompete cells of lower relative fitness ("losers"). We discuss the idea of super-competitors, mutant cells that expand at the expense of wild-type cells. Work on adult stem cells (ASCs) has revealed principles of neutral competition, wherein ASCs can be stochastically lost and replaced, and of biased competition, in which a winning ASC with a competitive advantage replaces its neighbors. Germline stem cells (GSCs) are ASCs that are uniquely endowed with the ability to produce gametes and, therefore, impact the next generation. Mechanisms of GSC competition have been elucidated by studies in Drosophila gonads, tunicates, and the mammalian testis. Competition between ASCs is thought to underlie various forms of cancer, including spermatocytic tumors in the human testis. Paternal age effect (PAE) disorders are caused by de novo mutations in human GSCs that increase their competitive ability and make them more likely to be inherited, leading to skeletal and craniofacial abnormalities in offspring. Given its widespread effects on human health, it is important to study GSC competition to elucidate how cells can become winners or losers.

Epithelial‑derived head and neck squamous tumourigenesis (Review)

Head and neck squamous cell carcinomas (HNSCCs), a heterogeneous group of cancers that arise from the mucosal epithelia cells in the head and neck areas, present great challenges in diagnosis, treatment and prognosis due to their complex aetiology and various clinical manifestations. Several factors, including smoking, alcohol consumption, oncogenic genes, growth factors, Epstein‑Barr virus and human papillomavirus infections can contribute to HNSCC development. The unpredictable tumour microenvironment adds to the complexity of managing HNSCC. Despite significant advances in therapies, the prediction of outcome after treatment for patients with HNSCC remains poor, and the 5‑year overall survival rate is low due to late diagnosis. Early detection greatly increases the chances of successful treatment. The present review aimed to bring together the latest findings related to the molecular mechanisms of HNSCC carcinogenesis and progression. Comprehensive genomic, transcriptomic, metabolomic, microbiome and proteomic analyses allow researchers to identify important biological markers such as genetic alterations, gene expression signatures and protein markers that drive HNSCC tumours. These biomarkers associated with the stages of initiation, progression and metastasis of cancer are useful in the management of patients with cancer in order to improve their life expectancy and quality of life.

Advancing cancer driver gene identification through an integrative network and pathway approach

OBJECTIVE

Cancer is a complex genetic disease characterized by the accumulation of various mutations, with driver genes playing a crucial role in cancer initiation and progression. Distinguishing driver genes from passenger mutations is essential for understanding cancer biology and discovering therapeutic targets. However, the majority of existing methods ignore the mutational heterogeneity and commonalities among patients, which hinders the identification of driver genes more effectively.

METHODS

This study introduces MCSdriver, a novel computational model that integrates network and pathway information to prioritize the identification of cancer driver genes. MCSdriver employs a bidirectional random walk algorithm to quantify the mutual exclusivity and functional relationships between mutated genes within patient cohorts. It calculates similarity scores based on a mutual exclusivity-weighted network and pathway coverage patterns, accounting for patient-specific heterogeneity and molecular profile similarity.

RESULTS

This approach enhances the accuracy and quality of driver gene identification. MCSdriver demonstrates superior performance in identifying cancer driver genes across four cancer types from The Cancer Genome Atlas, showing a higher F-score, Recall and Precision compared to existing ranking list-based and module-based models.

CONCLUSION

The MCSdriver model not only outperforms other models in identifying known cancer driver genes but also effectively identifies novel driver genes involved in cancer-related biological processes. The model's consideration of patient-specific heterogeneity and similarity in molecular profiles significantly enhances the accuracy and quality of driver gene identification. Validation through Gene Ontology enrichment analysis and literature mining further underscores its potential application value in personalized cancer therapy, offering a promising tool for advancing our understanding and treatment of cancer.

Prostate Cancer Progression Modeling Provides Insight into Dynamic Molecular Changes Associated with Progressive Disease States

Prostate cancer is a significant health concern and the most commonly diagnosed cancer in men worldwide. Understanding the complex process of prostate tumor evolution and progression is crucial for improved diagnosis, treatments, and patient outcomes. Previous studies have focused on unraveling the dynamics of prostate cancer evolution using phylogenetic or lineage analysis approaches. However, those approaches have limitations in capturing the complete disease process or incorporating genomic and transcriptomic variations comprehensively. In this study, we applied a novel computational approach to derive a prostate cancer progression model using multidimensional data from 497 prostate tumor samples and 52 tumor-adjacent normal samples obtained from The Cancer Genome Atlas study. The model was validated using data from an independent cohort of 545 primary tumor samples. By integrating transcriptomic and genomic data, our model provides a comprehensive view of prostate tumor progression, identifies crucial signaling pathways and genetic events, and uncovers distinct transcription signatures associated with disease progression. Our findings have significant implications for cancer research and hold promise for guiding personalized treatment strategies in prostate cancer.

SIGNIFICANCE

We developed and validated a progression model of prostate cancer using >1,000 tumor and normal tissue samples. The model provided a comprehensive view of prostate tumor evolution and progression.

When Do Tumours Develop? Neoplastic Processes Across Different Timescales: Age, Season and Round the Circadian Clock

While it is recognised that most, if not all, multicellular organisms harbour neoplastic processes within their bodies, the timing of when these undesirable cell proliferations are most likely to occur and progress throughout the organism's lifetime remains only partially documented. Due to the different mechanisms implicated in tumourigenesis, it is highly unlikely that this probability remains constant at all times and stages of life. In this article, we summarise what is known about this variation, considering the roles of age, season and circadian rhythm. While most studies requiring that level of detail be done on humans, we also review available evidence in other animal species. For each of these timescales, we identify mechanisms or biological functions shaping the variation. When possible, we show that evolutionary processes likely played a role, either directly to regulate the cancer risk or indirectly through trade-offs. We find that neoplastic risk varies with age in a more complex way than predicted by early epidemiological models: rather than resulting from mutations alone, tumour development is dictated by tissue- and age-specific processes. Similarly, the seasonal cycle can be associated with risk variation in some species with life-history events such as sexual competition or mating being timed according to the season. Lastly, we show that the circadian cycle influences tumourigenesis in physiological, pathological and therapeutic contexts. We also highlight two biological functions at the core of these variations across our three timescales: immunity and metabolism. Finally, we show that our understanding of the entanglement between tumourigenic processes and biological cycles is constrained by the limited number of species for which we have extensive data. Improving our knowledge of the periods of vulnerability to the onset and/or progression of (malignant) tumours is a key issue that deserves further investigation, as it is key to successful cancer prevention strategies.

4-Methyl-N-(Piperidin-1-Ylmethylene) Benzenesulfonamide (PMSA) Promotes Ferroptosis of Tumor Cells by Targeting the KEAP1-NRF2-GPX4 Axis

Background

We aimed to investigate the effect of 4-methyl-N-(piperidin-1-ylmethylene) benzenesulfonamide (PMSA) on tumor cell proliferation, migration, ferroptosis, and the potential molecular mechanism of ferroptosis in tumor cells.

Methods

PMSA was produced in the marine biomedical research institute of Guangdong Medical University (Zhanjiang, China) and used for tumor cells treatment. MTT and cell colony formation assays were used to measure the inhibition of tumor cell proliferation, the scratch assay was used to identified the suppression of tumor cell migration, the death of tumor cells was measured by Annexin-V-FITC/PI staining, the level of ferroptosis-relative lipid ROS in tumor cells was measured by flow cytometry and MDA detection kit, and the expression of ferroptosis-relative protein was measured by Western blot. The Discovery Studio system was used for molecular docking and the binding ability was measured by cellular thermal shift assay.

Results

The PMSA we produced inhibited tumor cell proliferation, colony formation, migration and triggered cell death, and Fer-1 could reverse these effects. The amount of ROS and MDA levels in tumor cells was also markedly raised by PMSA. PMSA treatment significantly reduced the expression of SLC7A11/XCT, NRF2, and GPX4 in tumor cells. The phosphorylation level of NRF2 was also decreased. Through molecular docking, it was discovered that PMSA could bind to NRF2 and thereby block its activity.

Conclusion

The KEAP1-NRF2-GPX4 axis was the target of PMSA's anti-tumor action, which results in ferroptosis of tumor cells. This demonstrated that the compound has the potential to be used as a candidate for anti-tumor drugs.

Somatic mutations in aging and disease

Time always leaves its mark, and our genome is no exception. Mutations in the genome of somatic cells were first hypothesized to be the cause of aging in the 1950s, shortly after the molecular structure of DNA had been described. Somatic mutation theories of aging are based on the fact that mutations in DNA as the ultimate template for all cellular functions are irreversible. However, it took until the 1990s to develop the methods to test if DNA mutations accumulate with age in different organs and tissues and estimate the severity of the problem. By now, numerous studies have documented the accumulation of somatic mutations with age in normal cells and tissues of mice, humans, and other animals, showing clock-like mutational signatures that provide information on the underlying causes of the mutations. In this review, we will first briefly discuss the recent advances in next-generation sequencing that now allow quantitative analysis of somatic mutations. Second, we will provide evidence that the mutation rate differs between cell types, with a focus on differences between germline and somatic mutation rate. Third, we will discuss somatic mutational signatures as measures of aging, environmental exposure, and activities of DNA repair processes. Fourth, we will explain the concept of clonally amplified somatic mutations, with a focus on clonal hematopoiesis. Fifth, we will briefly discuss somatic mutations in the transcriptome and in our other genome, i.e., the genome of mitochondria. We will end with a brief discussion of a possible causal contribution of somatic mutations to the aging process.