Targeting mutations in cancer

Prospects and challenges of neoantigen applications in oncology

Neoantigen, unique peptides resulting from tumor-specific mutations, represent a promising frontier in oncology for personalized cancer immunotherapy. Their unique features allow for the development of highly specific and effective cancer treatments, which can potentially overcome the limitations of conventional therapies. This paper explores the current prospects and challenges associated with the application of neoantigens in oncology. We examine the latest advances in neoantigen identification, vaccine development, and adoptive T cell therapy. Additionally, we discuss the obstacles related to neoantigen heterogeneity, immunogenicity prediction, and the tumor microenvironment. Through a comprehensive analysis of current research and clinical trials, this paper aims to provide a detailed overview of how neoantigens could revolutionize cancer treatment and the hurdles that must be overcome to realize their full potential.

Exploring the impact of estrogen-related receptor gamma on metabolism and disease

Estrogen-related receptor gamma (ERRγ) is a member of the ERR orphan nuclear receptor family which possesses three subtypes, α, β, and γ. ERRγ is reportedly predominantly expressed in metabolically active tissues and cells, which promotes positive and negative effects in different tissues. ERRγ overexpression in the liver, pancreas, and thyroid cells is related to liver cancer, oxidative stress, reactive oxygen species (ROS) regulation, and carcinoma. Reduced ERRγ expression in the brain, immune cells, tumor cells, and energy metabolism causes neurological dysfunction, gastric cancer, and obesity. ERRγ is a constitutive receptor; however, its transcriptional activity also depends on co-regulators, agonists, and antagonists, which, when after forming a complex, can play a role in targeting and treating diseases. Moreover, ERRγ has proven crucial in regulating cellular and metabolic activity. However, many functions mediated via ERRγ remain unknown and require further exploration. Hence, considering the importance of ERRγ, this review focuses on the critical findings and interactions between ERRγ and co-regulators, agonists, and antagonists alongside its relationship with downstream and upstream signaling pathways and diseases. This review highlights new findings and provides a path to understanding the current ideas and future studies on ERRγ-mediated cellular activity.

Expression-Driven Genetic Dependency Reveals Targets for Precision Medicine

Cancer cells are heterogeneous, each harboring distinct molecular aberrations and are dependent on different genes for their survival and proliferation. While successful targeted therapies have been developed based on driver DNA mutations, many patient tumors lack druggable mutations and have limited treatment options. Here, we hypothesize that new precision oncology targets may be identified through "expression-driven dependency", whereby cancer cells with high expression of a targeted gene are more vulnerable to the knockout of that gene. We introduce a Bayesian approach, BEACON, to identify such targets by jointly analyzing global transcriptomic and proteomic profiles with genetic dependency data of cancer cell lines across 17 tissue lineages. BEACON identifies known druggable genes, e.g., BCL2, ERBB2, EGFR, ESR1, MYC , while revealing new targets confirmed by both mRNA- and protein-expression driven dependency. Notably, the identified genes show an overall 3.8-fold enrichment for approved drug targets and enrich for druggable oncology targets by 7 to 10-fold. We experimentally validate that the depletion of GRHL2 , TP63 , and PAX5 effectively reduce tumor cell growth and survival in their dependent cells. Overall, we present the catalog of express-driven dependency targets as a resource for identifying novel therapeutic targets in precision oncology.

Pan-cancer and single-cell analysis reveal dual roles of lymphocyte activation gene-3 (LAG3) in cancer immunity and prognosis

Lymphocyte activating gene-3 (LAG3) is a distinctive T cell co-receptor that is expressed on the surface of lymphocytes. It plays a special inhibitory immune checkpoint role due to its unique domain and signaling pattern. Our aim is to explore the correlation between LAG3 in cancers and physiological processes related to a range of cancers, as well as build LAG3-related immunity and prognostic models. By comprehensively using of datasets and methods from TCGA, GTE-x and GEO databases, cBioPortal, HPA, Kaplan-Meier Plotter, Spearman, CellMinerTM, we delved deeper into the potential impact of the LAG3 in cancer development. These include expression differences, Localization of tumor cell subsets, immune infiltration, matrix infiltration, gene mutations, DNA methylation, signaling pathways and prognosis. Furthermore, we explored LAG3 interactions with different drugs. LAG3 is highly expressed in ACC (p < 0.001), BRCA (p < 0.001), DLBC (p < 0.001), ESCA (p < 0.001), GBM (p < 0.001), HNSC (p < 0.001), KIRC (p < 0.001), LGG (p < 0.001), LUAD (p < 0.01), LUSC (p < 0.001), PAAD (p < 0.001), PCPG (p < 0.01), SKCM (p < 0.001), STAD (p < 0.001), TGCT (p < 0.001) and THCA (p < 0.05), while lowly expressed in COAD (p < 0.001), LIHC (p < 0.05), OV (p < 0.001), PRAD (p < 0.001), READ (p < 0.001), UCEC (p < 0.001) and UCS (p < 0.001). High expression of LAG3 correlates with longer overall survival (OS) in BLCA (HR = 0.67, p < 0.05), CESC (HR = 0.3, p < 0.001), HNSC (HR = 0.67, p < 0.01), LUSC (HR = 0.71, p < 0.05), OV (HR = 0.65, p < 0.01), STAD (HR = 0.68, p < 0.05), and UCEC (HR = 0.57, p < 0.01). Conversely, in KIRC (HR = 1.85, p < 0.001), KIRP (HR = 2.81, p < 0.001), and THYM (HR = 8.92, p < 0.001), high LAG3 expression corresponds to shorter OS. Comprehensive results for recurrence-free survival (RFS) indicate that LAG3 acts as a protective factor in BLCA, CESC, OV, and UCEC. Moreover, LAG3 is widely expressed in tumor-associated lymphocytes, positively correlating with tumor immune scores and stromal scores, and significantly present in the C2 immune subtype across various tumors. High LAG3 expression correlates with increased immune infiltration. LAG3 shows associations with MSI, TMB, and the MMR system, participating in multiple signaling pathways including the T cell receptor pathway. It also demonstrates positive correlations with sensitivity to eleven different drugs. Unlike traditional inhibitory immune checkpoints, LAG3 exhibits dual roles in clinical and immune prognostication across pan-cancers, making it a significant predictive factor. In some cancers, LAG3 serves as a risk factor, indicating adverse clinical outcomes. Conversely, in BLCA, CESC, OV, and UCEC, LAG3 acts as a protective factor associated with longer patient survival. LAG3 demonstrates strong associations within tumor immunity, participating in a range of immune and inflammatory signaling pathways. Elevated levels of LAG3 are linked not only to T cell exhaustion but also to increased immune infiltration and polarization towards M1 macrophages.

Clinical and Technical Validation of OncoIndx® Assay-A Comprehensive Genome Profiling Assay for Pan-Cancer Investigations

Comprehensive next-generation sequencing (NGS) assays enable the identification of clinically relevant mutations, enhancing the capability for targeted therapeutic interventions. In addition, genomic alterations driving the oncogenic roadmap and leading to resistance mechanisms are reshaping precision oncology. We report the workflow and clinical and technical validation of the OncoIndx® NGS platform-a comprehensive genomic profiling (CGP)-based assay for pan-cancer investigation. We evaluated the concordance between the OncoIndx® test findings and clinically established hotspot detection using SeraSeq reference standards. OncoIndx is a hybridization capture-based NGS assay for the targeted deep sequencing of all exons and selected introns of 1080 cancer-related genes. We show the outcome in the form of tier I and tier II single nucleotide variants (SNVs), copy number alterations (CNAs), and specific gene fusions. OncoIndx® also informs genome-wide tumor mutational burden (TMB), microsatellite instability (MSI), homologous recombination deficiency (HRD), and genomic loss of heterozygosity (gLOH). A total of 63 samples were utilized for validation with reference standards, clinical samples, and orthogonal assessment for genomic alterations. In addition, 49 cross-laboratory samples were validated for microsatellite instability (MSI), and for the tumor mutation burden (TMB), 18 samples as reference standards, 6 cross-laboratory samples, and 29 TCGA samples were utilized. We show a maximum clinical sensitivity of 98% and a positive predictive value (PPV) of 100% for the clinically actionable genomic variants detected by the assay. In addition, we demonstrate analytical validation with the performance of the assay, limit of detection (LoD), precision, and orthogonal concordance for various types of SVs, CNAs, genomic rearrangements, and complex biomarkers like TMB, MSI, and HRD. The assay offers reliable genomic predictions with the high-precision detection of actionable variants, validated by established reference standards.

The fork remodeler helicase-like transcription factor in cancer development: all at once

The Helicase-like Transcription Factor (HLTF) is a member of the SNF2-family of fork remodelers, primarily studied for its capacity to provide DNA Damage Tolerance (DDT) and to induce replication fork reversal (RFR). HLTF is recruited at stalled forks where both its ATPase motor and HIP116 Rad5p N-terminal (HIRAN) domains are necessary for regulating its interaction with DNA. HIRAN bestows specificity to ssDNA 3'-end and imparts branch migration as well as DNA remodeling capabilities facilitating damage repair. Both expression regulation and mutation rate affect HLTF activity. Gene hypermethylation induces loss of HLTF function, in particular in colorectal cancer (CRC), implying a tumour suppressor role. Surprisingly, a correlation between hypermethylation and HLTF mRNA upregulation has also been observed, even within the same cancer type. In many cancers, both complex mutation patterns and the presence of gene Copy Number Variations (CNVs) have been reported. These conditions affect the amount of functional HLTF and question the physiological role of this fork remodeler. This review offers a systematic collection of the presently strewed information regarding HLTF, its structural and functional characteristics, the multiple roles in DDT and the regulation in cancer progression highlighting new research perspectives.

Comprehensive investigation of long non-coding RNA HOTAIR polymorphisms and cancer risk: a current meta-analysis encompassing 96,458 participants

Cancer ranks as the second leading cause of mortality worldwide, prompting extensive investigations into factors contributing to its development. Among these factors, genetic variations, known as genotypic polymorphisms, have been identified as significant influencers in the susceptibility to various types of cancer. Recent research has focused on exploring the connection between polymorphisms in the Long Non-coding RNA HOTAIR and cancer risk. However, the results from these studies have been inconsistent, leading to ambiguity and controversy. To address this uncertainty, we conducted a systematic analysis by gathering relevant studies from PubMed, EMBASE, and Google Scholar. Specifically, we focused on three well-studied polymorphisms within the HOTAIR lncRNA (HOTAIR rs920778 C > T, HOTAIR rs1899663 G > T, HOTAIR rs4759314 A > G) and their association with cancer risk. Our meta-analysis included data from 48 case-control studies involving 42,321 cases and 54,137 controls. The results of our updated meta-analysis revealed a significant correlation between HOTAIR rs1899663 G > T and HOTAIR rs4759314 A > G polymorphisms and overall cancer risk, particularly in the homozygous and recessive genetic models. Subgroup analysis further revealed that these associations were notably pronounced in the Asian population but not observed in the Iranian population. Furthermore, our findings underscore the potential of HOTAIR polymorphisms as diagnostic markers for overall cancer risk, particularly in gynecological cancers, precisely, HOTAIR rs1899663 G > T polymorphism in breast cancer. In conclusion, our systematic analysis provides compelling evidence that Long Non-coding RNA HOTAIR polymorphisms are linked to cancer risk, particularly in certain populations and cancer types, suggesting their potential clinical relevance as diagnostic indicators.

Functional Investigations of p53 Acetylation Enabled by Heterobifunctional Molecules

Post-translational modifications (PTMs) dynamically regulate the critical stress response and tumor suppressive functions of p53. Among these, acetylation events mediated by multiple acetyltransferases lead to differential target gene activation and subsequent cell fate. However, our understanding of these events is incomplete due to, in part, the inability to selectively and dynamically control p53 acetylation. We recently developed a heterobifunctional small molecule system, AceTAG, to direct the acetyltransferase p300/CBP for targeted protein acetylation in cells. Here, we expand AceTAG to leverage the acetyltransferase PCAF/GCN5 and apply these tools to investigate the functional consequences of targeted p53 acetylation in human cancer cells. We demonstrate that the recruitment of p300/CBP or PCAF/GCN5 to p53 results in distinct acetylation events and differentiated transcriptional activities. Further, we show that chemically induced acetylation of multiple hotspot p53 mutants results in increased stabilization and enhancement of transcriptional activity. Collectively, these studies demonstrate the utility of AceTAG for functional investigations of protein acetylation.

In Silico Screening, Molecular Dynamics Simulation and Binding Free Energy Identify Single-Point Mutations That Destabilize p53 and Reduce Binding to DNA

Considering p53's pivotal role as a tumor suppressor protein, proactive identification and characterization of potentially harmful p53 mutations are crucial before they appear in the population. To address this, four computational prediction tools-SIFT, Polyphen-2, PhD-SNP, and MutPred2-utilizing sequence-based and machine-learning algorithms, were employed to identify potentially deleterious p53 nsSNPs (nonsynonymous single nucleotide polymorphisms) that may impact p53 structure, dynamics, and binding with DNA. These computational methods identified three variants, namely, C141Y, C238S, and L265P, as detrimental to p53 stability. Furthermore, molecular dynamics (MD) simulations revealed that all three variants exhibited heightened structural flexibility compared to the native protein, especially the C141Y and L265P mutations. Consequently, due to the altered structure of mutant p53, the DNA-binding affinity of all three variants decreased by approximately 1.8 to 9.7 times compared to wild-type p53 binding with DNA (14 μM). Notably, the L265P mutation exhibited an approximately ten-fold greater reduction in binding affinity. Consequently, the presence of the L265P mutation in p53 could pose a substantial risk to humans. Given that p53 regulates abnormal tumor growth, this research carries significant implications for surveillance efforts and the development of anticancer therapies.

Multi-omics and clustering analyses reveal the mechanisms underlying unmet needs for patients with lung adenocarcinoma and identify potential therapeutic targets

BACKGROUND

The cancer genome contains several driver mutations. However, in some cases, no known drivers have been identified; these remaining areas of unmet needs, leading to limited progress in cancer therapy. Whole-genome sequencing (WGS) can identify non-coding alterations associated with the disease. Consequently, exploration of non-coding regions using WGS and other omics data such as ChIP-sequencing (ChIP-seq) to discern novel alterations and mechanisms related to tumorigenesis have been attractive these days.

METHODS

Integrated multi-omics analyses, including WGS, ChIP-seq, DNA methylation, and RNA-sequencing (RNA-seq), were conducted on samples from patients with non-clinically actionable genetic alterations (non-CAGAs) in lung adenocarcinoma (LUAD). Second-level cluster analysis was performed to reinforce the correlations associated with patient survival, as identified by RNA-seq. Subsequent differential gene expression analysis was performed to identify potential druggable targets.

RESULTS

Differences in H3K27ac marks in non-CAGAs LUAD were found and confirmed by analyzing RNA-seq data, in which mastermind-like transcriptional coactivator 2 (MAML2) was suppressed. The down-regulated genes whose expression was correlated to MAML2 expression were associated with patient prognosis. WGS analysis revealed somatic mutations associated with the H3K27ac marks in the MAML2 region and high levels of DNA methylation in MAML2 were observed in tumor samples. The second-level cluster analysis enabled patient stratification and subsequent analyses identified potential therapeutic target genes and treatment options.

CONCLUSIONS

We overcome the persistent challenges of identifying alterations or driver mutations in coding regions related to tumorigenesis through a novel approach combining multi-omics data with clinical information to reveal the molecular mechanisms underlying non-CAGAs LUAD, stratify patients to improve patient prognosis, and identify potential therapeutic targets. This approach may be applicable to studies of other cancers with unmet needs.

Assessing the Cost-Effectiveness of Next-Generation Sequencing as a Biomarker Testing Approach in Oncology and Policy Implications: A Literature Review

OBJECTIVE

A key hurdle in broader next-generation sequencing (NGS) biomarker testing access in oncology is the ongoing debate on NGS's cost-effectiveness. We conducted a systematic review of existing evidence of the costs of NGS as a biomarker testing strategy in oncology and developed policy suggestions.

METHODS

We searched multiple databases for studies reporting cost comparisons and cost-effectiveness of NGS across oncology indications and geographies between 2017 and 2022, inclusive. Inclusion criteria were established based on indication and type of cost-effectiveness analysis provided. We validated analyses and policy recommendations with 5 payer/policy maker interviews in the United States, Europe, and United Kingdom.

RESULTS

Of the 634 identified studies, 29 met inclusion criteria, spanning 12 countries and 6 indications. Cost comparisons of NGS were evaluated using 3 methodologies: (1) comparison of direct testing costs, (2) comparison of holistic testing costs, and (3) comparison of long-term patient outcomes and costs. Targeted panel testing (2-52 genes) was considered cost-effective when 4+ genes were assessed, and larger panels (hundreds of genes) were generally not cost-effective. Holistic analysis demonstrated that NGS reduces turnaround time, healthcare staff requirements, number of hospital visits, and hospital costs. Finally, studies evaluating NGS testing including the cost of targeted therapies generally found the incremental cost-effectiveness ratio to be above common thresholds but highlighted valuable patient benefits.

CONCLUSIONS

Current literature supports NGS's cost-effectiveness as an oncology biomarker testing strategy under specific conditions. These findings underscore the need to develop policies to support holistic assessment of NGS to ensure appropriate reimbursement and access.

Regulation, functional impact, and therapeutic targeting of APOBEC3A in cancer

Enzymes of the apolipoprotein B mRNA editing catalytic polypeptide like (APOBEC) family are cytosine deaminases that convert cytosine to uracil in DNA and RNA. Among these proteins, APOBEC3 sub-family members, APOBEC3A (A3A) and APOBEC3B (A3B), are prominent sources of mutagenesis in cancer cells. The aberrant expression of A3A and A3B in cancer cells leads to accumulation of mutations with specific single-base substitution (SBS) signatures, characterized by C→T and C→G changes, in a number of tumor types. In addition to fueling mutagenesis, A3A and A3B, particularly A3A, induce DNA replication stress, DNA damage, and chromosomal instability through their catalytic activities, triggering a range of cellular responses. Thus, A3A/B have emerged as key drivers of genome evolution during cancer development, contributing to tumorigenesis, tumor heterogeneity, and therapeutic resistance. Yet, the expression of A3A/B in cancer cells presents a cancer vulnerability that can be exploited therapeutically. In this review, we discuss the recent studies that shed light on the mechanisms regulating A3A expression and the impact of A3A in cancer. We also review recent advances in the development of A3A inhibitors and provide perspectives on the future directions of A3A research.

Advances in Personalized Oncology

Advances in next-generation sequencing (NGS) have catalyzed a paradigm shift in cancer treatment, steering the focus from conventional, organ-specific protocols to precision medicine. Emerging targeted therapies offer a cutting-edge approach to cancer treatment, while companion diagnostics play an essential role in aligning therapeutic choices with specific molecular changes identified through NGS. Despite these advances, interpreting the clinical implications of a rapidly expanding catalog of genetic mutations remains a challenge. The selection of therapies in the presence of multiple mutations requires careful clinical judgment, supported by quality-centric genomic testing that emphasizes actionable mutations. Molecular tumor boards can play an increasing role in assimilating genomic data into clinical trials, thereby refining personalized treatment approaches and improving patient outcomes.

Copy number alterations: a catastrophic orchestration of the breast cancer genome

Breast cancer (BCa) is a prevalent malignancy that predominantly affects women around the world. Somatic copy number alterations (CNAs) are tumor-specific amplifications or deletions of DNA segments that often drive BCa development and therapy resistance. Hence, the complex patterns of CNAs complement BCa classification systems. In addition, understanding the precise contributions of CNAs is essential for tailoring personalized treatment approaches. This review highlights how tumor evolution drives the acquisition of CNAs, which in turn shape the genomic landscapes of BCas. It also discusses advanced methodologies for identifying recurrent CNAs, studying CNAs in BCa and their clinical impact.

Lipid-based nanosystems: the next generation of cancer immune therapy

Immunotherapy has become an important part of the oncotherapy arsenal. Its applicability in various cancer types is impressive, as well as its use of endogenous mechanisms to achieve desired ends. However, off-target or on-target-off-tumor toxicity, limited activity, lack of control in combination treatments and, especially for solid tumors, low local accumulation, have collectively limited clinical use thereof. These limitations are partially alleviated by delivery systems. Lipid-based nanoparticles (NPs) have emerged as revolutionary carriers due to favorable physicochemical characteristics, with specific applications and strengths particularly useful in immunotherapeutic agent delivery. The aim of this review is to highlight the challenges faced by immunotherapy and how lipid-based NPs have been, and may be further utilized to address such challenges. We discuss recent fundamental and clinical applications of NPs in a range of areas and provide a detailed discussion of the main obstacles in immune checkpoint inhibition therapies, adoptive cellular therapies, and cytokine therapies. We highlight how lipid-based nanosystems could address these through either delivery, direct modulation of the immune system, or targeting of the immunosuppressive tumor microenvironment. We explore advanced and emerging liposomal and lipid nanoparticle (LNP) systems for nucleic acid delivery, intrinsic and extrinsic stimulus-responsive formulations, and biomimetic lipid-based nanosystems in immunotherapy. Finally, we discuss the key challenges relating to the clinical use of lipid-based NP immunotherapies, suggesting future research directions for the near term to realize the potential of these innovative lipid-based nanosystems, as they become the crucial steppingstone towards the necessary enhancement of the efficacy of immunotherapy.

Enhancing cancer therapy: the integration of oncolytic virus therapy with diverse treatments

As one of the significant challenges to human health, cancer has long been a focal point in medical treatment. With ongoing advancements in the field of medicine, numerous methodologies for cancer therapy have emerged, among which oncolytic virus therapy has gained considerable attention. However, oncolytic viruses still exhibit limitations. Combining them with various therapies can further enhance the efficacy of cancer treatment, offering renewed hope for patients. In recent research, scientists have recognized the promising prospect of amalgamating oncolytic virus therapy with diverse treatments, potentially surmounting the restrictions of singular approaches. The central concept of this combined therapy revolves around leveraging oncolytic virus to incite localized tumor inflammation, augmenting the immune response for immunotherapeutic efficacy. Through this approach, the patient's immune system can better recognize and eliminate cancer cells, simultaneously reducing tumor evasion mechanisms against the immune system. This review delves deeply into the latest research progress concerning the integration of oncolytic virus with diverse treatments and its role in various types of cancer therapy. We aim to analyze the mechanisms, advantages, potential challenges, and future research directions of this combination therapy. By extensively exploring this field, we aim to instill renewed hope in the fight against cancer.

Emerging Therapeutic Strategies to Overcome Drug Resistance in Cancer Cells

The rise of drug resistance in cancer cells presents a formidable challenge in modern oncology, necessitating the exploration of innovative therapeutic strategies. This review investigates the latest advancements in overcoming drug resistance mechanisms employed by cancer cells, focusing on emerging therapeutic modalities. The intricate molecular insights into drug resistance, including genetic mutations, efflux pumps, altered signaling pathways, and microenvironmental influences, are discussed. Furthermore, the promising avenues offered by targeted therapies, combination treatments, immunotherapies, and precision medicine approaches are highlighted. Specifically, the synergistic effects of combining traditional cytotoxic agents with molecularly targeted inhibitors to circumvent resistance pathways are examined. Additionally, the evolving landscape of immunotherapeutic interventions, including immune checkpoint inhibitors and adoptive cell therapies, is explored in terms of bolstering anti-tumor immune responses and overcoming immune evasion mechanisms. Moreover, the significance of biomarker-driven strategies for predicting and monitoring treatment responses is underscored, thereby optimizing therapeutic outcomes. For insights into the future direction of cancer treatment paradigms, the current review focused on prevailing drug resistance challenges and improving patient outcomes, through an integrative analysis of these emerging therapeutic strategies.

Naturally Occurring Phytochemicals to Target Breast Cancer Cell Signaling

Almost 70% of clinically used antineoplastic drugs are originated from natural products such as plants, marine organism, and microorganisms and some of them are also structurally modified natural products. The naturally occurring drugs may specifically act as inducers of selective cytotoxicity, anti-metastatic, anti-mutagenic, anti-angiogenesis, antioxidant accelerators, apoptosis inducers, autophagy inducers, and cell cycle inhibitors in cancer therapy. Precisely, several reports have demonstrated the involvement of naturally occurring anti-breast cancer drugs in regulating the expression of oncogenic and tumor suppressors associated with carcinogen metabolism and signaling pathways. Anticancer therapies based on nanotechnology have the potential to improve patient outcomes through targeted therapy, improved drug delivery, and combination therapies. This paper has reviewed the current treatment for breast cancer and the potential disadvantages of those therapies, besides the various mechanism used by naturally occurring phytochemicals to induce apoptosis in different types of breast cancer. Along with this, the contribution of nanotechnology in improving the effectiveness of anticancer drugs was also reviewed. With the development of sciences and technologies, phytochemicals derived from natural products are continuously discovered; however, the search for novel natural products as chemoprevention drugs is still ongoing, especially for the advanced stage of breast cancer. Continued research and development in this field hold great promise for advancing cancer care and improving patient outcomes.

Correlation Analysis of Genetic Mutations and Galectin Levels in Breast Cancer Patients

Galectins are innate immune system regulators associated with disease progression in cancer. This paper aims to investigate the correlation between mutated cancer-critical genes and galectin levels in breast cancer patients to determine whether galectins and genetic profiles can be used as biomarkers for disease and potential therapy targets. Prisma Health Cancer Institute's Biorepository provided seventy-one breast cancer samples, including all four stages spanning the major molecular subtypes and histologies. Hotspot mutation statuses of cancer-critical genes were determined using multiplex PCR in tumor samples from the same patients by Precision Genetics and the University of South Carolina Functional Genomics Core Facility. The galectin-1, -3, and -9 levels in patients' sera were analyzed using Enzyme-linked Immunosorbent Assay (ELISA). An analysis was performed using JMP software to compare mean and median serum galectin levels between samples with and without specific cancer-critical genes, including pooled t-test, Wilcoxon Rank Sum Test, ANOVA, and Steel Dwass Test (α=0.05). Our analysis indicates that KIT mutations correlate with elevated serum levels of galectin-9 in patients with breast cancer. In patients with Luminal A subtype, FLT3 mutation correlates with lower serum galectin-1 and -9 levels and TP53 mutations correlate with higher serum galectin-3 levels. Patients with invasive ductal carcinoma had significantly higher serum galectin-3 levels than patients with ductal carcinoma in situ. Patients with both TP53 and PIK3CA mutations exhibit elevated serum galectin-3 levels, while patients with one or neither mutation show no significant difference in serum galectin-3 levels. In addition, metastatic breast cancer samples were more likely to have a KIT or PIK3CA mutation compared to primary breast cancer samples. The relationship between genetic mutations and galectin levels has the potential to identify appropriate candidates for combined therapy, targeting genetic mutations and galectins. Further understanding of the effect of genetic mutations and galectin levels on cancer progression and metastasis could aid in the search for biomarkers for breast cancer diagnosis, disease progression, and prognosis.

Multivalent DNAzyme agents for cleaving folded RNA

Multivalent recognition and binding of biological molecules is a natural phenomenon that increases the binding stability (avidity) without decreasing the recognition specificity. In this study, we took advantage of this phenomenon to increase the efficiency and maintain high specificity of RNA cleavage by DNAzymes (Dz). We designed a series of DNA constructs containing two Dz agents, named here bivalent Dz devices (BDD). One BDD increased the cleavage efficiency of a folded RNA fragment up to 17-fold in comparison with the Dz of a conventional design. Such an increase was achieved due to both the improved RNA binding and the increased probability of RNA cleavage by the two catalytic cores. By moderating the degree of Dz agent association in BDD, we achieved excellent selectivity in differentiating single-base mismatched RNA, while maintaining relatively high cleavage rates. Furthermore, a trivalent Dz demonstrated an even greater efficiency than the BDD in cleaving folded RNA. The data suggests that the cooperative action of several RNA-cleaving units can significantly improve the efficiency and maintain high specificity of RNA cleavage, which is important for the development of Dz-based gene knockdown agents.

Transfer Learning in Cancer Genetics, Mutation Detection, Gene Expression Analysis, and Syndrome Recognition

Artificial intelligence (AI), encompassing machine learning (ML) and deep learning (DL), has revolutionized medical research, facilitating advancements in drug discovery and cancer diagnosis. ML identifies patterns in data, while DL employs neural networks for intricate processing. Predictive modeling challenges, such as data labeling, are addressed by transfer learning (TL), leveraging pre-existing models for faster training. TL shows potential in genetic research, improving tasks like gene expression analysis, mutation detection, genetic syndrome recognition, and genotype-phenotype association. This review explores the role of TL in overcoming challenges in mutation detection, genetic syndrome detection, gene expression, or phenotype-genotype association. TL has shown effectiveness in various aspects of genetic research. TL enhances the accuracy and efficiency of mutation detection, aiding in the identification of genetic abnormalities. TL can improve the diagnostic accuracy of syndrome-related genetic patterns. Moreover, TL plays a crucial role in gene expression analysis in order to accurately predict gene expression levels and their interactions. Additionally, TL enhances phenotype-genotype association studies by leveraging pre-trained models. In conclusion, TL enhances AI efficiency by improving mutation prediction, gene expression analysis, and genetic syndrome detection. Future studies should focus on increasing domain similarities, expanding databases, and incorporating clinical data for better predictions.

lncRNAs and cyclin-dependent kinases: Unveiling their critical roles in cancer progression

Long non-coding RNAs (lncRNAs) are a diverse class of RNA molecules that do not code for proteins but play critical roles in gene regulation. One such role involves the modulation of cell cycle progression and proliferation through interactions with cyclin-dependent kinases (CDKs), key regulators of cell division. Dysregulation of CDK activity is a hallmark of cancer, contributing to uncontrolled cell growth and tumor formation. These lncRNA-CDK interactions are part of a complex network of molecular mechanisms underlying cancer pathogenesis, involving various signaling pathways and regulatory circuits. Understanding the interplay between lncRNAs, CDKs, and cancer biology holds promise for developing novel therapeutic strategies targeting these molecular targets for more effective cancer treatment. Furthermore, targeting CDKs, key cell cycle progression and proliferation regulators, offers another avenue for disrupting cancer pathways and overcoming drug resistance. This can open new possibilities for individualized treatment plans and focused therapeutic interventions.

Single-Cell Profiling Reveals the Impact of Genetic Alterations on the Differentiation of Inflammation-Induced Murine Colon Tumors

Genetic mutations and chronic inflammation of the colon contribute to the development of colorectal cancer (CRC). Using a murine model of inflammation-induced colon tumorigenesis, we determined how genetic mutations alter colon tumor cell differentiation. Inflammation induced by enterotoxigenic Bacteroides fragilis (ETBF) colonization of multiple intestinal neoplasia (MinApcΔ716/+) mice triggers loss of heterozygosity of Apc causing colon tumor formation. Here, we report that the addition of BRAFV600E mutation (BRAFF-V600ELgr5tm1(Cre/ERT2)CleMinApcΔ716/+, BLM) or knocking out Msh2 (Msh2LoxP/LoxPVil1-creMinApcΔ716/+, MSH2KO) in the Min model altered colon tumor differentiation. Using single-cell RNA sequencing, we uncovered the differences between BLM, Min, and MSH2KO tumors at a single-cell resolution. BLM tumors showed an increase in differentiated tumor epithelial cell lineages and a reduction in the tumor stem cell population. Interestingly, the tumor stem cell population of BLM tumors had revival colon stem cell characteristics with low WNT signaling and an increase in RevCSC marker gene expression. In contrast, MSH2KO tumors were characterized by an increased tumor stem cell population that had higher WNT signaling activity compared to Min tumors. Furthermore, overall BLM tumors had higher expression of transcription factors that drive differentiation, such as Cdx2, than Min tumors. Using RNA velocity, we identified additional potential regulators of BLM tumor differentiation such as NDRG1. The role of CDX2 and NDRG1 as putative regulators for BLM tumor cell differentiation was verified using organoids derived from BLM tumors. Our results demonstrate the critical connections between genetic mutations and cell differentiation in inflammation-induced colon tumorigenesis. Understanding such roles will deepen our understanding of inflammation-associated colon cancer.

Genomic dissection and mutation-specific target discovery for breast cancer PIK3CA hotspot mutations

BACKGROUND

Recent advancements in high-throughput genomics and targeted therapies have provided tremendous potential to identify and therapeutically target distinct mutations associated with cancers. However, to date the majority of targeted therapies are used to treat all functional mutations within the same gene, regardless of affected codon or phenotype.

RESULTS

In this study, we developed a functional genomic analysis workflow with a unique isogenic cell line panel bearing two distinct hotspot PIK3CA mutations, E545K and H1047R, to accurately identify targetable differences between mutations within the same gene. We performed RNA-seq and ATAC-seq and identified distinct transcriptomic and epigenomic differences associated with each PIK3CA hotspot mutation. We used this data to curate a select CRISPR knock out screen to identify mutation-specific gene pathway vulnerabilities. These data revealed AREG as a E545K-preferential target that was further validated through in vitro analysis and publicly available patient databases.

CONCLUSIONS

Using our multi-modal genomics framework, we discover distinct differences in genomic regulation between PIK3CA hotspot mutations, suggesting the PIK3CA mutations have different regulatory effects on the function and downstream signaling of the PI3K complex. Our results demonstrate the potential to rapidly uncover mutation specific molecular targets, specifically AREG and a proximal gene regulatory region, that may provide clinically relevant therapeutic targets. The methods outlined provide investigators with an integrative strategy to identify mutation-specific targets for the treatment of other oncogenic mutations in an isogenic system.

Individualized Pharmacotherapy Utilizing Genetic Biomarkers and Novel In Vitro Systems As Predictive Tools for Optimal Drug Development and Treatment

In the area of drug development and clinical pharmacotherapy, a profound understanding of the pharmacokinetics and potential adverse reactions associated with the drug under investigation is paramount. Essential to this endeavor is a comprehensive understanding about interindividual variations in absorption, distribution, metabolism, and excretion (ADME) genetics and the predictive capabilities of in vitro systems, shedding light on metabolite formation and the risk of adverse drug reactions (ADRs). Both the domains of pharmacogenomics and the advancement of in vitro systems are experiencing rapid expansion. Here we present an update on these burgeoning fields, providing an overview of their current status and illuminating potential future directions. SIGNIFICANCE STATEMENT: There is very rapid development in the area of pharmacogenomics and in vitro systems for predicting drug pharmacokinetics and risk for adverse drug reactions. We provide an update of the current status of pharmacogenomics and developed in vitro systems on these aspects aimed to achieve a better personalized pharmacotherapy.

Glutathione Depletion and Stalwart Anticancer Activity of Metallotherapeutics Inducing Programmed Cell Death: Opening a New Window for Cancer Therapy

The cellular defense system against exogenous substances makes therapeutics inefficient as intracellular glutathione (GSH) exhibits an astounding antioxidant activity in scavenging reactive oxygen species (ROS) or reactive nitrogen species (RNS) or other free radicals produced by the therapeutics. In the cancer cell microenvironment, the intracellular GSH level becomes exceptionally high to fight against oxidative stress created by the production of ROS/RNS or any free radicals, which are the byproducts of intracellular redox reactions or cellular respiration processes. Thus, in order to maintain redox homeostasis for survival of cancer cells and their rapid proliferation, the GSH level starts to escalate. In this circumstance, the administration of anticancer therapeutics is in vain, as the elevated GSH level reduces their potential by reduction or by scavenging the ROS/RNS they produce. Therefore, in order to augment the therapeutic potential of anticancer agents against elevated GSH condition, the GSH level must be depleted by hook or by crook. Hence, this Review aims to compile precisely the role of GSH in cancer cells, the importance of its depletion for cancer therapy and examples of anticancer activity of a few selected metal complexes which are able to trigger cancer cell death by depleting the GSH level.

Enasidenib-induced hepatitis in an individual with Type II D2-hydroxyglutaric aciduria

Type II D-2-Hydroxyglutaric aciduria (T2D2HGA) is caused by a gain-of-function pathogenic variant in Isocitrate Dehydrogenase 2 (IDH2). Patients with T2D2HGA commonly present with developmental delay, seizures, cardiomyopathy, and arrhythmias. The recently approved IDH2-inhibitor Enasidenib targets the p.Arg140Gln pathogenic IDH2 variant and decreases production of D2HGA. We present a 7-year-old female with T2D2HGA due to the p.Arg140Gln variant. She was diagnosed at 3-years-old after presenting with global developmental delay, leukoencephalopathy, communicating hydrocephalus, seizures, and dilated cardiomyopathy. At age 3 years 11 months, 50 mg Enasidenib daily was initiated. Primary outcomes included seizure frequency, hospital admissions, development, and cardiac structure. Laboratories were monitored biweekly for common Enasidenib side effects. Our patient tolerated Enasidenib well. Urine 2-HGA decreased significantly from 244 mg/g creatinine to undetectable within 2 weeks of treatment. Inpatient admissions decreased from 8 during the 2 years preceding treatment to 1 during treatment. She has been seizure-free since Enasidenib initiation. Echocardiography showed improvement in dilated cardiomyopathy with normal left ventricular systolic function. Developmental assessment demonstrated improvements in gross motor, fine motor, language, and socialization domains. Treatment was complicated by mild elevations in alanine transaminase (118 IU/L, range 0-28) and creatine kinase (334 U/L, range 45-198) that resolved by decreasing Enasidenib dosing frequency to three times weekly. Enasidenib is a viable treatment for Type II D2HGA with benefits including developmental gains, fewer acute medical interventions, and cardiomyopathy improvement. While drug-induced hepatitis is a novel adverse effect of Enasidenib, it can be ameliorated by decreasing dose frequency.

Genomic deletions explain the generation of alternative BRAF isoforms conferring resistance to MAPK inhibitors in melanoma

Resistance to MAPK inhibitors (MAPKi), the main cause of relapse in BRAF-mutant melanoma, is associated with the production of alternative BRAF mRNA isoforms (altBRAFs) in up to 30% of patients receiving BRAF inhibitor monotherapy. These altBRAFs have been described as being generated by alternative pre-mRNA splicing, and splicing modulation has been proposed as a therapeutic strategy to overcome resistance. In contrast, we report that altBRAFs are generated through genomic deletions. Using different in vitro models of altBRAF-mediated melanoma resistance, we demonstrate the production of altBRAFs exclusively from the BRAF V600E allele, correlating with corresponding genomic deletions. Genomic deletions are also detected in tumor samples from melanoma and breast cancer patients expressing altBRAFs. Along with the identification of altBRAFs in BRAF wild-type and in MAPKi-naive melanoma samples, our results represent a major shift in our understanding of mechanisms leading to the generation of BRAF transcripts variants associated with resistance in melanoma.

The importance of protein domain mutations in cancer therapy

Cancer is a complex disease that is caused by multiple genetic factors. Researchers have been studying protein domain mutations to understand how they affect the progression and treatment of cancer. These mutations can significantly impact the development and spread of cancer by changing the protein structure, function, and signalling pathways. As a result, there is a growing interest in how these mutations can be used as prognostic indicators for cancer prognosis. Recent studies have shown that protein domain mutations can provide valuable information about the severity of the disease and the patient's response to treatment. They may also be used to predict the response and resistance to targeted therapy in cancer treatment. The clinical implications of protein domain mutations in cancer are significant, and they are regarded as essential biomarkers in oncology. However, additional techniques and approaches are required to characterize changes in protein domains and predict their functional effects. Machine learning and other computational tools offer promising solutions to this challenge, enabling the prediction of the impact of mutations on protein structure and function. Such predictions can aid in the clinical interpretation of genetic information. Furthermore, the development of genome editing tools like CRISPR/Cas9 has made it possible to validate the functional significance of mutants more efficiently and accurately. In conclusion, protein domain mutations hold great promise as prognostic and predictive biomarkers in cancer. Overall, considerable research is still needed to better define genetic and molecular heterogeneity and to resolve the challenges that remain, so that their full potential can be realized.

Deciphering fibroblast-induced drug resistance in non-small cell lung carcinoma through patient-derived organoids in agarose microwells

Patient-derived organoids (PDOs) serve as invaluable 3D tumor models, retaining the histological complexity and genetic heterogeneity found in primary tumors. However, the limitation of small sample volumes and the lack of tailored platforms have hindered the research using PDOs. Within the tumor microenvironment, cancer-associated fibroblasts play a pivotal role in influencing drug sensitivity. In this study, we introduce an agarose microwell platform designed for PDO-based tumor and tumor microenvironment models, enabling rapid drug screening and resistance studies with small sample volumes. These microwells, constructed using 3D printing molds, feature a U-shaped bottom and 200 μm diameter. We successfully generated co-culture spheroids of non-small cell lung carcinoma (NSCLC) cells, including NCI-H358 or A549, and NSCLC PDOs F231 or F671 with fibroblast cell line, WI-38. Our results demonstrate the production of uniformly-sized spheroids (coefficient of variation <30%), high viability (>80% after 1 week), and fibroblast-induced drug resistance. The PDOs maintained their viability (>81% after 2 weeks) and continued to proliferate. Notably, when exposed to adagrasib, a KRASG12C inhibitor, we observed reduced cytotoxicity in KRASG12C-mutant spheroids when co-cultured with fibroblasts or their supernatant. The fibroblast supernatant sustained proliferative signals in tumor models. Taking into account the physical features, viability, and drug resistance acquired through supernatants from the fibroblasts, our platform emerges as a suitable platform for in vitro tumor modeling and the evaluation of drug efficacy using patient-derived tissues.

ERK pathway agonism for cancer therapy: evidence, insights, and a target discovery framework

At least 40% of human cancers are associated with aberrant ERK pathway activity (ERKp). Inhibitors targeting various effectors within the ERKp have been developed and explored for over two decades. Conversely, a substantial body of evidence suggests that both normal human cells and, notably to a greater extent, cancer cells exhibit susceptibility to hyperactivation of ERKp. However, this vulnerability of cancer cells remains relatively unexplored. In this review, we reexamine the evidence on the selective lethality of highly elevated ERKp activity in human cancer cells of varying backgrounds. We synthesize the insights proposed for harnessing this vulnerability of ERK-associated cancers for therapeutical approaches and contextualize these insights within established pharmacological cancer-targeting models. Moreover, we compile the intriguing preclinical findings of ERK pathway agonism in diverse cancer models. Lastly, we present a conceptual framework for target discovery regarding ERKp agonism, emphasizing the utilization of mutual exclusivity among oncogenes to develop novel targeted therapies for precision oncology.

Evidence of direct interaction between cisplatin and the caspase-cleaved prostate apoptosis response-4 tumor suppressor

Prostate apoptosis response-4 (Par-4) tumor suppressor protein has gained attention as a potential therapeutic target owing to its unique ability to selectively induce apoptosis in cancer cells, sensitize them to chemotherapy and radiotherapy, and mitigate drug resistance. It has recently been reported that Par-4 interacts synergistically with cisplatin, a widely used anticancer drug. However, the mechanistic details underlying this relationship remain elusive. In this investigation, we employed an array of biophysical techniques, including circular dichroism spectroscopy, dynamic light scattering, and UV-vis absorption spectroscopy, to characterize the interaction between the active caspase-cleaved Par-4 (cl-Par-4) fragment and cisplatin. Additionally, elemental analysis was conducted to quantitatively assess the binding of cisplatin to the protein, utilizing inductively coupled plasma-optical emission spectroscopy and atomic absorption spectroscopy. Our findings provide evidence of direct interaction between cl-Par-4 and cisplatin, and reveal a binding stoichiometry of 1:1. This result provides insights that could be useful in enhancing the efficacy of cisplatin-based and tumor suppressor-based cancer therapies.

Analytical validation and clinical utilization of K-4CARE™: a comprehensive genomic profiling assay with personalized MRD detection

Background: Biomarker testing has gradually become standard of care in precision oncology to help physicians select optimal treatment for patients. Compared to single-gene or small gene panel testing, comprehensive genomic profiling (CGP) has emerged as a more time- and tissue-efficient method. This study demonstrated in-depth analytical validation of K-4CARE, a CGP assay that integrates circulating tumor DNA (ctDNA) tracking for residual cancer surveillance. Methods: The assay utilized a panel of 473 cancer-relevant genes with a total length of 1.7 Mb. Reference standards were used to evaluate limit of detection (LOD), concordance, sensitivity, specificity and precision of the assay to detect single nucleotide variants (SNVs), small insertion/deletions (Indels), gene amplification and fusion, microsatellite instability (MSI) and tumor mutational burden (TMB). The assay was then benchmarked against orthogonal methods using 155 clinical samples from 10 cancer types. In selected cancers, top tumor-derived somatic mutations, as ranked by our proprietary algorithm, were used to detect ctDNA in the plasma. Results: For detection of somatic SNVs and Indels, gene fusion and amplification, the assay had sensitivity of >99%, 94% and >99% respectively, and specificity of >99%. Detection of germline variants also achieved sensitivity and specificity of >99%. For TMB measurement, the correlation coefficient between whole-exome sequencing and our targeted panel was 97%. MSI analysis when benchmarked against polymerase chain reaction method showed sensitivity of 94% and specificity of >99%. The concordance between our assay and the TruSight Oncology 500 assay for detection of somatic variants, TMB and MSI measurement was 100%, 89%, and 98% respectively. When CGP-informed mutations were used to personalize ctDNA tracking, the detection rate of ctDNA in liquid biopsy was 79%, and clinical utility in cancer surveillance was demonstrated in 2 case studies. Conclusion: K-4CARE™ assay provides comprehensive and reliable genomic information that fulfills all guideline-based biomarker testing for both targeted therapy and immunotherapy. Integration of ctDNA tracking helps clinicians to further monitor treatment response and ultimately provide well-rounded care to cancer patients.

Drug development advances in human genetics-based targets

Drug development is a long and costly process, with a high degree of uncertainty from the identification of a drug target to its market launch. Targeted drugs supported by human genetic evidence are expected to enter phase II/III clinical trials or be approved for marketing more quickly, speeding up the drug development process. Currently, genetic data and technologies such as genome-wide association studies (GWAS), whole-exome sequencing (WES), and whole-genome sequencing (WGS) have identified and validated many potential molecular targets associated with diseases. This review describes the structure, molecular biology, and drug development of human genetics-based validated beneficial loss-of-function (LOF) mutation targets (target mutations that reduce disease incidence) over the past decade. The feasibility of eight beneficial LOF mutation targets (PCSK9, ANGPTL3, ASGR1, HSD17B13, KHK, CIDEB, GPR75, and INHBE) as targets for drug discovery is mainly emphasized, and their research prospects and challenges are discussed. In conclusion, we expect that this review will inspire more researchers to use human genetics and genomics to support the discovery of novel therapeutic drugs and the direction of clinical development, which will contribute to the development of new drug discovery and drug repurposing.

Molecular diagnostics tailoring personalized cancer therapy-an oncologist's view

Medical oncology is rapidly evolving with the implementation of personalized, targeted therapies. Advances in molecular diagnostics and the biologic understanding of cancer pathophysiology led to the identification of specific genetic alterations as drivers of cancer progression. Further, improvements in drug development enable the direct interference with these pathways, which allow tailoring personalized treatments based on a distinct molecular characterization of tumors. Thereby, we are currently experiencing a paradigm-shift in the treatment of cancers towards cancer-type agnostic, molecularly targeted, personalized therapies. However, this concept has several important hurdles and limitations to overcome to ultimately increase the proportion of patients benefitting from the precision oncology approach. These include the assessment of clinical relevancy of identified alterations, capturing and interpreting levels of heterogeneity based on intra-tumoral or time-dependent molecular evolution, and challenges in the practical implementation of precision oncology in routine clinical care. In the present review, we summarize the current state of cancer-agnostic precision oncology, discuss the concept of molecular tumor boards, and consider current limitations of personalized cancer therapy. Further, we provide an outlook towards potential future developments including the implementation of functionality assessments of identified genetic alterations and the broader use of liquid biopsies in order to obtain more comprehensive and longitudinal genetic information that might guide personalized cancer therapy in the future.

Genomic dissection and mutation-specific target discovery for breast cancer PIK3CA hotspot mutations

Background

Recent advancements in high-throughput genomics and targeted therapies have provided tremendous potential to identify and therapeutically target distinct mutations associated with cancers. However, to date the majority of targeted therapies are used to treat all functional mutations within the same gene, regardless of affected codon or phenotype.

Results

In this study, we developed a functional genomic analysis workflow with a unique isogenic cell line panel bearing two distinct hotspot PIK3CA mutations, E545K and H1047R, to accurately identify targetable differences between mutations within the same gene. We performed RNA-seq and ATAC-seq and identified distinct transcriptomic and epigenomic differences associated with each PIK3CA hotspot mutation. We used this data to curate a select CRISPR knock out screen to identify mutation-specific gene pathway vulnerabilities. These data revealed AREG as a E545K-preferential target that was further validated through in vitro analysis and publicly available patient databases.

Conclusions

Using our multi-modal genomics framework, we discover distinct differences in genomic regulation between PIK3CA hotspot mutations, suggesting the PIK3CA mutations have different regulatory effects on the function and downstream signaling of the PI3K complex. Our results demonstrate the potential to rapidly uncover mutation specific molecular targets, specifically AREG and a proximal gene regulatory region, that may provide clinically relevant therapeutic targets. The methods outlined provide investigators with an integrative strategy to identify mutation-specific targets for the treatment of other oncogenic mutations in an isogenic system.

Driver gene KRAS aggravates cancer-associated stroke outcomes

The incidence of cancer-associated stroke has increased with the prolonged survival times of cancer patients. Recent genetic studies have led to progress in cancer therapeutics, but relationships between oncogenic mutations and stroke remain elusive. Here, we focused on the driver gene KRAS, which is the predominant RAS isoform mutated in multiple cancer types, in cancer associated stroke study. KRASG13D/- and parental human colorectal carcinoma HCT116 cells were inoculated into mice that were then subjected to a photochemically-induced thrombosis model to establish ischemic stroke. We found that cancer inoculation exacerbated neurological deficits after stroke. Moreover, mice inoculated with KRASG13D/- cells showed worse neurological deficits after stroke compared with mice inoculated with parental cells. Stroke promoted tumor growth, and the KRASG13D/- allele enhanced this growth. Brain RNA sequencing analysis and serum ELISA showed that chemokines and cytokines mediating pro-inflammatory responses were upregulated in mice inoculated with KRASG13D/- cells compared with those inoculated with parental cells. STAT3 phosphorylation was promoted following ischemic stroke in the KRASG13D/- group compared with in the parental group, and STAT3 inhibition significantly ameliorated stroke outcomes by mitigating microglia/macrophage polarization. Finally, we compared the prognosis and mortality of colorectal cancer patients with or without stroke onset between 1 January 2007 and 31 December 2020 using a hospital-based cancer registry and found that colorectal cancer patients with stroke onset within 3 months after cancer diagnosis had a worse prognosis. Our work suggests an interplay between KRAS and ischemic stroke that may offer insight into future treatments for cancer-associated stroke.

Single-cell profiling reveals the impact of genetic alterations on the differentiation of inflammation-induced colon tumors

Genetic mutations and chronic inflammation of the colon contribute to the development of colorectal cancer (CRC). Using a murine model of inflammation-induced colon tumorigenesis, we determined how genetic mutations alter colon tumor cell differentiation. Inflammation induced by enterotoxigenic Bacteroides fragilis (ETBF) colonization of multiple intestinal neoplasia (Min ApcΔ716/+ ) mice triggers loss of heterozygosity of Apc causing colon tumor formation. Here, we report that the addition of BRAF V600E mutation ( BRAF FV600E Lgr5 tm1(Cre/ERT2)Cle Min ApcΔ716/+ , BLM) or knocking out Msh2 ( Msh2 LoxP/LoxP Vil1-cre Min ApcΔ716/+ , MSH2KO) in the Min model altered colon tumor differentiation. Using single cell RNA-sequencing, we uncovered the differences between BLM, Min, and MSH2KO tumors at a single cell resolution. BLM tumors showed an increase in differentiated tumor epithelial cell lineages and a reduction in the stem cell population. In contrast, MSH2KO tumors were characterized by an increased stem cell population that had higher WNT signaling activity compared to Min tumors. Additionally, comparative analysis of single-cell transcriptomics revealed that BLM tumors had higher expression of transcription factors that drive differentiation, such as Cdx2, than Min tumors. Using RNA velocity, we were able to identify additional potential regulators of BLM tumor differentiation such as NDRG1. The role of CDX2 and NDRG1 as putative regulators for BLM tumor cell differentiation was verified using organoids derived from BLM tumors. Our results demonstrate the critical connections between genetic mutations and cell differentiation in inflammation-induced colon tumorigenesis. Understanding such roles will deepen our understanding of inflammation-associated colon cancer.

Genetic alterations shape innate immune cells to foster immunosuppression and cancer immunotherapy resistance

Cancer immunotherapy, particularly immune checkpoint inhibitors, has opened a new avenue for cancer treatment following the durable clinical benefits. Despite the clinical successes across several cancer types, primary or acquired resistance might eventually lead to cancer progression in patients with clinical responses. Hence, to broaden the clinical applicability of these treatments, a detailed understanding of the mechanisms limiting the efficacy of cancer immunotherapy is needed. Evidence provided thus far has implicated immunosuppressive innate immune cells infiltrating the tumor microenvironment as key players in immunotherapy resistance. According to the available data, genetic alterations can shape the innate immune response to promote immunotherapy resistance and tumor progression. Herein, this review has discussed the current understanding of the underlying mechanisms where genetic alterations modulate the innate immune milieu to drive immunosuppression and immunotherapy resistance.

Genetic Testing Enhances the Precision Diagnosis and Treatment of Breast Cancer

The contemporary comprehension of breast cancer has progressed to the molecular level. As a heterogeneous malignancy, conventional pathological diagnosis and histological classification could no longer meet the needs of precisely managing breast cancer. Genetic testing based on gene expression profiles and gene mutations has emerged and substantially contributed to the precise diagnosis and treatment of breast cancer. Multigene assays (MGAs) are explored for early-stage breast cancer patients, aiding the selection of adjuvant therapy and predicting prognosis. For metastatic breast cancer patients, testing specific genes indicates potentially effective antitumor agents. In this review, genetic testing in early-stage and metastatic breast cancer is summarized, as well as the advantages and challenges of genetic testing in breast cancer.

TRPS1, a New Promising Marker for Assessment of Distant Metastatic Breast Cancer

This article reviewed the identification of breast cancer in the distant metastatic setting through traditional immunohistochemical markers, such as mammaglobin and GATA3, compared with the novel immunohistochemical stain, Trichorhinophalangeal syndrome-1 (TRPS1). We review previous studies evaluating TRPS1 staining, which were conducted using cytology specimens, as well as our recently conducted study evaluating this stain using surgical tissue samples, both from primary and distant metastatic invasive breast carcinoma. In summary, although no immunohistochemical stain is 100% specific or sensitive, in the metastatic setting where tissue available for ancillary studies is limited, TRPS1 was a reliable and even a standalone marker for breast origin, particularly in cases of triple-negative breast cancer.

Application of single-cell sequencing to the research of tumor microenvironment

Single-cell sequencing is a technique for detecting and analyzing genomes, transcriptomes, and epigenomes at the single-cell level, which can detect cellular heterogeneity lost in conventional sequencing hybrid samples, and it has revolutionized our understanding of the genetic heterogeneity and complexity of tumor progression. Moreover, the tumor microenvironment (TME) plays a crucial role in the formation, development and response to treatment of tumors. The application of single-cell sequencing has ushered in a new age for the TME analysis, revealing not only the blueprint of the pan-cancer immune microenvironment, but also the heterogeneity and differentiation routes of immune cells, as well as predicting tumor prognosis. Thus, the combination of single-cell sequencing and the TME analysis provides a unique opportunity to unravel the molecular mechanisms underlying tumor development and progression. In this review, we summarize the recent advances in single-cell sequencing and the TME analysis, highlighting their potential applications in cancer research and clinical translation.

A three-stage eccDNA based molecular profiling significantly improves the identification, prognosis assessment and recurrence prediction accuracy in patients with glioma

Glioblastoma (GBM) progression is influenced by intratumoral heterogeneity. Emerging evidence has emphasized the pivotal role of extrachromosomal circular DNA (eccDNA) in accelerating tumor heterogeneity, particularly in GBM. However, the eccDNA landscape of GBM has not yet been elucidated. In this study, we first identified the eccDNA profiles in GBM and adjacent tissues using circle- and RNA-sequencing data from the same samples. A three-stage model was established based on eccDNA-carried genes that exhibited consistent upregulation and downregulation trends at the mRNA level. Combinations of machine learning algorithms and stacked ensemble models were used to improve the performance and robustness of the three-stage model. In stage 1, a total of 113 combinations of machine learning algorithms were constructed and validated in multiple external cohorts to accurately distinguish between low-grade glioma (LGG) and GBM in patients with glioma. The model with the highest area under the curve (AUC) across all cohorts was selected for interpretability analysis. In stage 2, a total of 101 combinations of machine learning algorithms were established and validated for prognostic prediction in patients with glioma. This prognostic model performed well in multiple glioma cohorts. Recurrent GBM is invariably associated with aggressive and refractory disease. Therefore, accurate prediction of recurrence risk is crucial for developing individualized treatment strategies, monitoring patient status, and improving clinical management. In stage 3, a large-scale GBM cohort (including primary and recurrent GBM samples) was used to fit the GBM recurrence prediction model. Multiple machine learning and stacked ensemble models were fitted to select the model with the best performance. Finally, a web tool was developed to facilitate the clinical application of the three-stage model.

Assessing the Clinical Utility of Liquid Biopsies Across 5 Potential Indications From Therapy Selection to Population Screening: A Review

Importance

There has been great enthusiasm for the emerging technology of molecular-based tests to detect and quantify tumor DNA circulating in the bloodstream, colloquially known as a liquid biopsy. However, less attention has been given to how their clinical utility depends on the indication for testing, which includes a range of clinical situations, each presenting unique challenges.

Observations

Five indications for circulating tumor DNA (ctDNA) blood testing were considered. (1) For therapy selection, ctDNA tests can identify genetic alterations in patients with cancer amenable to targeted therapy, but most patients do not have a targetable alteration. (2) For response to therapy, the absence of residual tumor DNA following cancer surgery could reduce the use of adjuvant chemotherapy, but it is unclear that this will happen in practice. (3) For disease surveillance following cancer treatment, ctDNA tests may well detect cancer recurrence before symptoms appear, yet earlier intervention may have no effect on mortality. (4) For diagnosis of suspected cancer, ctDNA tests are able to identify some symptomatic cancers, but how they add to the conventional diagnostic evaluation is unknown. (5) For screening for cancer, multicancer tests can detect many types of cancer, but their low sensitivity for early-stage tumors raises questions as to whether screening can help patients live longer or live better.

Conclusions and Relevance

Circulating tumor DNA tests are being promoted for multiple indications. Numerous studies are ongoing, but randomized clinical trials of their effect on patient-centered outcomes are rare. While these tests have the potential to improve care in selected indications, this must be proven, as they will add cost, complexity, and unintended adverse effects for patients.

Molecular Profiling and Targeted Therapies in Gliomas

PURPOSE OF REVIEW

Molecular profiling enables the evaluation of genetic alterations for the diagnosis and classification of gliomas and the selection of appropriate therapies. This review summarizes the current role of molecular profiling and targeted therapies for gliomas.

RECENT FINDINGS

Molecular profiling is an integral part of the 2021 WHO classification of gliomas. Progress in the development of targeted therapies remains limited due to many factors including the presence of the blood-brain barrier and issues of tumor heterogeneity. Nonetheless, advances have been made with the IDH1/2 inhibitor vorasidenib for IDH-mutant grade 2 gliomas, the combination of dabrafenib and trametinib for BRAFV600E mutated gliomas, and the therapies for subsets of patients with fusions and H3K27M-altered diffuse midline gliomas. While there has been progress in the use of molecular profiling for the classification and treatment of gliomas, much work remains for targeted therapies to realize their potential.

A Scoping Review on Tyrosine Kinase Inhibitors in Cats: Current Evidence and Future Directions

Tyrosine kinase inhibitors (TKIs) have become invaluable in the treatment of human and canine malignancies, but their role in feline oncology is less defined. While toceranib phosphate and masitinib mesylate are licensed for use in dogs, no TKI is yet approved for cats. This review systematically maps the research conducted on the expression of tyrosine kinases in neoplastic and non-neoplastic domestic feline tissues, as well as the in vitro/in vivo use of TKIs in domestic cats. We identify and discuss knowledge gaps and speculate on the further research and potential indications for TKI use in cats. A comprehensive search of three electronic databases and relevant paper reference lists identified 139 studies meeting the inclusion criteria. The most commonly identified tumors were mast cell tumors (MCTs), mammary and squamous cell carcinomas and injection-site sarcomas. Based on the current literature, toceranib phosphate appears to be the most efficacious TKI in cats, especially against MCTs. Exploring the clinical use of TKIs in mammary carcinomas holds promise. Despite the progress, currently, the evidence falls short, underscoring the need for further research to discover new indications in feline oncology and to bridge the knowledge gaps between human and feline medicine.

Cytotoxic Potential of Novel Quinoline Derivative: 11-(1,4-Bisaminopropylpiperazinyl)5-methyl-5H-indolo[2,3-b]quinoline against Different Cancer Cell Lines via Activation and Deactivation of the Expression of Some Proteins

The current study evaluated the cytotoxic activity of 11-(1,4-bisaminopropylpiperazinyl)5-methyl-5H-indolo[2,3-b]quinoline (BAPPN), a novel derivative of 5-methyl-5H-indolo[2,3-b]quinoline, against hepatocellular carcinoma (HepG2), colon carcinoma (HCT-116), breast (MCF-7), and lung (A549) cancer cell lines and the possible molecular mechanism through which it exerts its cytotoxic activity. BAPPN was synthesized and characterized with FT-IR and NMR spectroscopy. The binding affinity scores of BAPPN for caspase-3 PDB: 7JL7 was -7.836, with an RMSD of 1.483° A. In silico screening of ADME properties indicated that BAPPN showed promising oral bioavailability records in addition to their high gastrointestinal absorption and blood-brain barrier penetrability. BAPPN induced cytotoxicity, with IC50 values of 3.3, 23, 3.1, and 9.96 μg/mL against cancer cells HepG2, HCT-116, MCF-7, and A549, respectively. In addition, it induced cell injury and morphological changes in ultracellular structure, including cellular delayed activity, vanishing of membrane blebbing, microvilli, cytoplasmic condensation, and shrunken nucleus with more condensed chromatin autophagosomes. Furthermore, BAPPN significantly increased the protein expression of caspase-3 and tumor suppressor protein (P53). However, it significantly reduced the secretion of vascular endothelial growth factor (VEGF) protein into the medium and decreased the protein expression of proliferation cellular nuclear antigen (PCNA) and Ki67 in HepG2, HCT-116, MCF-7, and A549 cells. This study indicates that BAPPN has cytotoxic action against liver, colon, breast, and lung cancer cell lines via the up-regulation of apoptotic proteins, caspase-3 and P53, and the downregulation of proliferative proteins, VEGF, PCNA, and Ki67.