Cancer genome landscapes

A phase Ia study of the MEK1/2 inhibitor PD-0325901 with the c-MET inhibitor crizotinib in patients with advanced solid cancers

BACKGROUND

Single-agent MEK1/2 inhibition has been disappointing in clinical trials targeting RAS mutant (MT) cancers, probably due to upstream receptor activation, resulting in resistance. We previously found that dual c-MET/MEK1/2 inhibition attenuated RASMT colorectal cancer (CRC) xenograft growth. In this study, we assessed safety of MEK1/2 inhibitor PD-0325901 with c-MET inhibitor crizotinib and determined the optimal biological doses for subsequent clinical trials.

METHODS

In this dose-escalation phase I trial, patients with advanced solid tumours received PD-0325901 with crizotinib, using a rolling-6 design to determine the maximum tolerable dose (MTD) and safety/tolerability. Blood samples for pharmacokinetics and skin biopsies were collected.

RESULTS

Twenty-five patients were recruited in 4 cohorts up to doses of crizotinib 200 mg B.D continuously with PD-0325901 8 mg B.D, days 1-21 every 28 days. One in six patients exhibited a dose-limiting toxicity at this dose level. Drug-related adverse events were in keeping with single-agent toxicity profiles. The best clinical response was stable disease in seven patients (29%).

CONCLUSIONS

PD-0325901/crizotinib can be given together at pharmacologically-active doses. The MTD for PD-0325901/crizotinib was 8 mg B.D (days 1-21) and 200 mg B.D continuously in a 28-days cycle. The combination was further explored with an alternate MEK1/2 inhibitor in RASMT CRC patients.

EUDRACT-NUMBER

2014-000463-40.

In vivo targeted and deterministic single-cell malignant transformation

Why does a normal cell possibly harboring genetic mutations in oncogene or tumor suppressor genes becomes malignant and develops a tumor is a subject of intense debate. Various theories have been proposed but their experimental test has been hampered by the unpredictable and improbable malignant transformation of single cells. Here, using an optogenetic approach we permanently turn on an oncogene (KRASG12V) in a single cell of a zebrafish brain that, only in synergy with the transient co-activation of a reprogramming factor (VENTX/NANOG/OCT4), undergoes a deterministic malignant transition and robustly and reproducibly develops within 6 days into a full-blown tumor. The controlled way in which a single cell can thus be manipulated to give rise to cancer lends support to the 'ground state theory of cancer initiation' through 'short-range dispersal' of the first malignant cells preceding tumor growth.

Addressing Challenges in Targeted Therapy for Metastatic Colorectal Cancer

This review article aims to address the challenges associated with targeted therapy for the treatment of metastatic colorectal cancer (mCRC). We will first provide an overview of approved targeted therapies for treating mCRC, which include antiangiogenic therapy, as well as inhibitors of EGFR, BRAFV600E, HER2 inhibitors, and immune checkpoints. Second, we discuss the different mechanisms of primary resistance, including tumor heterogeneity, both as inter-patient and intra-patient heterogeneity, and mechanisms of secondary resistance which include: driver oncogene alterations, downstream or parallel bypass signaling, presence of co-dominant driver oncogenes, tumor lineage plasticity, and epithelial to mesenchymal transition. Resistance mechanisms towards the different drug classes targeting mCRC are discussed in detail. Strategies to overcome resistance primarily involve combination of therapies, although this approach is typically linked to increased drug toxicity, manifesting as on and off-target effects. Moreover, the cost and accessibility of targeted therapies pose significant challenges for diverse populations. Addressing these challenges necessitates further research efforts aimed at optimizing the use of targeted therapy in mCRC. Integration of genomic biomarkers, such as sequencing and liquid biopsy, into routine clinical practice holds promise in enhancing treatment outcomes. In conclusion, this comprehensive review underscores the complex challenges encountered in targeted therapy for mCRC.

Endoplasmic Reticulum Stress and Its Role in Metabolic Reprogramming of Cancer

Background/Objectives: Endoplasmic reticulum (ER) stress occurs when ER homeostasis is disrupted, leading to the accumulation of misfolded or unfolded proteins. This condition activates the unfolded protein response (UPR), which aims to restore balance or trigger cell death if homeostasis cannot be achieved. In cancer, ER stress plays a key role due to the heightened metabolic demands of tumor cells. This review explores how metabolomics can provide insights into ER stress-related metabolic alterations and their implications for cancer therapy. Methods: A comprehensive literature review was conducted to analyze recent findings on ER stress, metabolomics, and cancer metabolism. Studies examining metabolic profiling of cancer cells under ER stress conditions were selected, with a focus on identifying potential biomarkers and therapeutic targets. Results: Metabolomic studies highlight significant shifts in lipid metabolism, protein synthesis, and oxidative stress management in response to ER stress. These metabolic alterations are crucial for tumor adaptation and survival. Additionally, targeting ER stress-related metabolic pathways has shown potential in preclinical models, suggesting new therapeutic strategies. Conclusions: Understanding the metabolic impact of ER stress in cancer provides valuable opportunities for drug development. Metabolomics-based approaches may help identify novel biomarkers and therapeutic targets, enhancing the effectiveness of antitumor therapies.

From virtual to reality: innovative practices of digital twins in tumor therapy

BACKGROUND

As global cancer incidence and mortality rise, digital twin technology in precision medicine offers new opportunities for cancer treatment.

OBJECTIVE

This study aims to systematically analyze the current applications, research trends, and challenges of digital twin technology in tumor therapy, while exploring future directions.

METHODS

Relevant literature up to 2024 was retrieved from PubMed, Web of Science, and other databases. Data visualization was performed using R and VOSviewer software. The analysis includes the research initiation and trends, funding models, global research distribution, sample size analysis, and data processing and artificial intelligence applications. Furthermore, the study investigates the specific applications and effectiveness of digital twin technology in tumor diagnosis, treatment decision-making, prognosis prediction, and personalized management.

RESULTS

Since 2020, research on digital twin technology in oncology has surged, with significant contributions from the United States, Germany, Switzerland, and China. Funding primarily comes from government agencies, particularly the National Institutes of Health in the U.S. Sample size analysis reveals that large-sample studies have greater clinical reliability, while small-sample studies emphasize technology validation. In data processing and artificial intelligence applications, the integration of medical imaging, multi-omics data, and AI algorithms is key. By combining multimodal data integration with dynamic modeling, the accuracy of digital twin models has been significantly improved. However, the integration of different data types still faces challenges related to tool interoperability and limited standardization. Specific applications of digital twin technology have shown significant advantages in diagnosis, treatment decision-making, prognosis prediction, and surgical planning.

CONCLUSION

Digital twin technology holds substantial promise in tumor therapy by optimizing personalized treatment plans through integrated multimodal data and dynamic modeling. However, the study is limited by factors such as language restrictions, potential selection bias, and the relatively small number of published studies in this emerging field, which may affect the comprehensiveness and generalizability of our findings. Moreover, issues related to data heterogeneity, technical integration, and data privacy and ethics continue to impede its broader clinical application. Future research should promote international collaboration, establish unified interdisciplinary standards, and strengthen ethical regulations to accelerate the clinical translation of digital twin technology in cancer treatment.

Defining the genome-wide mutagenic impact of APOBEC3 enzymes

Somatic mutations drive cancer initiation and tumor evolution. Therefore, the etiology of mutagenesis in cancer is important to preventative and treatment strategies. Somatic mutagenesis in cancer is a multifactorial process and includes both endogenous and exogenous sources of mutations. One recently recognized source of mutagenesis in cancer is the innate immune APOBEC3 family of enzymes, which catalyze cytosine deamination to restrict viral infection but can aberrantly act on the cellular genome, resulting in mutations. Single base substitution (SBS) signatures, or mutational patterns, identified in cancer genomes have demonstrated widespread mutagenesis caused by APOBEC3 enzymes throughout human tumors. To comprehensively define the consequences of APOBEC3 mutagenesis, we developed an experimental pipeline for prospective analysis of genome-wide mutations caused by APOBEC3 activity. This pipeline can be adapted to analyze additional sources of mutagenesis across a spectrum of cells.

Intratumoral heterogeneity and drug resistance in cancer

Intratumoral heterogeneity is the main cause of tumor treatment failure, varying across disease sites (spatial heterogeneity) and polyclonal properties of tumors that evolve over time (temporal heterogeneity). As our understanding of intratumoral heterogeneity, the formation of which is mainly related to the genomic instability, epigenetic modifications, plastic gene expression, and different microenvironments, plays a substantial role in drug-resistant as far as tumor metastasis and recurrence. Understanding the role of intratumoral heterogeneity, it becomes clear that a single therapeutic agent or regimen may only be effective for subsets of cells with certain features, but not for others. This necessitates a shift from our current, unchanging treatment approach to one that is tailored against the killing patterns of cancer cells in different clones. In this review, we discuss recent evidence concerning global perturbations of intratumoral heterogeneity, associations of specific intratumoral heterogeneity in lung cancer, the underlying mechanisms of intratumoral heterogeneity potentially leading to formation, and how it drives drug resistance. Our findings highlight the most up-to-date progress in intratumoral heterogeneity and its role in mediating tumor drug resistance, which could support the development of future treatment strategies.

Tryptophan-2,3-Dioxygenase as a Therapeutic Target in Digestive System Diseases

Tryptophan (Trp) is an essential amino acid that must be acquired exclusively through dietary intake. The metabolism of tryptophan plays a critical role in maintaining immune homeostasis and tolerance, as well as in preventing excessive inflammatory responses. Tryptophan-2,3-dioxygenase (TDO2) is a tetrameric heme protein and serves as one of the pivotal rate-limiting enzymes in the first step of tryptophan metabolism. Dysregulation of TDO2 expression has been observed in various digestive system diseases, encompassing those related to the oral cavity, esophagus, liver, stomach, pancreas, and colon and rectum. Digestive system diseases are the most common clinical diseases, with complex clinical manifestations and interrelated symptoms, and have become a research hotspot in the field of medicine. Studies have demonstrated that aberrant TDO2 expression is closely associated with various clinical manifestations and disease outcomes in patients with digestive system disorders. Consequently, TDO2 has garnered increasing recognition as a promising therapeutic target for digestive system diseases in recent years, attracting growing attention. This article provides a brief overview of the role of TDO2 in the tryptophan pathway, emphasizing its significant involvement in diseases of the digestive system. Strategies targeting TDO2 through specific inhibitors suggest considerable promise in enhancing therapeutic outcomes for digestive diseases. Thus, this review concludes by discussing recent advancements in the development of TDO2 inhibitors. We believe that targeted inhibition of TDO2 combined with immunotherapy, the screening of a large number of natural products, and the assistance of artificial intelligence in drug design will be important directions for developing more effective TDO2 inhibitors and improving treatment outcomes in the future.

In vivo vectorization and delivery systems for gene therapies and RNA-based therapeutics in oncology

Gene and RNA-based therapeutics represent a promising frontier in oncology, enabling targeted modulation of tumor-associated genes and proteins. This review explores the latest advances in payload vectorization and delivery systems developed for in vivo cancer treatments. We discuss viral and non-viral organic particles, including lipid based nanoparticles and polymeric structures, for the effective transport of plasmids, siRNA, and self-amplifying RNA therapeutics. Their physicochemical properties, strategies to overcome intracellular barriers, and innovations in cell-based carriers and engineered extracellular vesicles are highlighted. Moreover, we consider oncolytic viruses, novel viral capsid modifications, and approaches that refine tumor targeting and immunomodulation. Ongoing clinical trials and regulatory frameworks guide future directions and emphasize the need for safe, scalable production. The potential convergence of these systems with combination therapies paves the way toward personalized cancer medicine.

Diverse somatic genomic alterations in single neurons in chronic traumatic encephalopathy

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease that is linked to exposure to repetitive head impacts (RHI), yet little is known about its pathogenesis. Applying two single-cell whole-genome sequencing methods to hundreds of neurons from prefrontal cortex of 15 individuals with CTE, and 4 with RHI without CTE, revealed increased somatic single-nucleotide variants in CTE, resembling a pattern previously reported in Alzheimer's disease (AD). Furthermore, we discovered remarkably high burdens of somatic small insertions and deletions in a subset of CTE individuals, resembling a known pattern, ID4, also found in AD. Our results suggest that neurons in CTE experience stereotyped mutational processes shared with AD; the absence of similar changes in RHI neurons without CTE suggests that CTE involves mechanisms beyond RHI alone.

Machine learning identifies clinical tumor mutation landscape pathways of resistance to checkpoint inhibitor therapy in NSCLC

BACKGROUND

Immune checkpoint inhibitors (CPIs) have revolutionized cancer therapy for several tumor indications. However, a substantial fraction of patients treated with CPIs derive no benefit or have short-lived responses to CPI therapy. Identifying patients who are most likely to benefit from CPIs and deciphering resistance mechanisms is therefore essential for developing adjunct treatments that can abrogate tumor resistance.

PATIENTS AND METHODS

In this study, we used a machine learning approach that used the US-based nationwide de-identified Flatiron Health and Foundation Medicine non-small cell lung carcinoma (NSCLC) clinico-genomic database to identify genomic markers that predict clinical responses to CPI therapy. In total, we analyzed data from 4,433 patients with NSCLC.

RESULTS

Analysis of pretreatment genomic data from 1,511 patients with NSCLC identified. Of the 36 genomic signatures identified, 33 exhibited strong predictive capacity for CPI response (n=1150) compared with chemotherapy response (n=361), while three signatures were prognostic. These 36 genetic signatures had in common a core set of four genes (BRAF, BRIP1, FGF10, and FLT1). Interestingly, we observed that some (n=19) of the genes in the signatures (eg, TP53, EZH2, KEAP1 and FGFR2) had alternative mutations with contrasting clinical outcomes to CPI therapy. Finally, the genetic signatures revealed multiple biological pathways involved in CPI response, including MAPK, PDGF, IL-6 and EGFR signaling.

CONCLUSIONS

In summary, we found several genomic markers and pathways that provide insight into biological mechanisms affecting response to CPI therapy. The analyses identified novel targets and biomarkers that have the potential to provide candidates for combination therapies or patient enrichment strategies, which could increase response rates to CPI therapy in patients with NSCLC.

Chimerism: A whole new perspective in gene regulation

The diversity of molecular entities emerging from a single gene are recognized. Several studies have thus established the cellular role(s) of transcript variants and protein isoforms. A step ahead in challenging the central dogma towards expanding molecular diversity is the identification of fusion genes, chimeric transcripts and chimeric proteins that harbor sequences from more than one gene. The mechanisms for generation of chimeras largely follow similar patterns across all levels of gene regulation but also have interdependence and mutual exclusivity. Whole genome and RNA-seq technologies supported by development of computational algorithms and programs for processing datasets have increasingly enabled the identification of fusion genes and chimeric transcripts, while the discovery of chimeric proteins is as yet more subtle. Earlier thought to be associated with cellular transformation, the contribution of chimeric molecules to normal physiology is also realized and found to influence the expression of their parental genes and regulate cellular pathways. This review offers a collective and comprehensive overview of cellular chimeric entities encompassing the mechanisms involved in their generation, insights on their evolution, functions in gene regulation and their current and novel clinical applications.

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

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

Sarcomatoid Carcinoma of the Ileum Mimicking a Gastrointestinal Stromal Tumor (GIST) Presenting With Primary Subfertility: A Report of a Rare Case

Sarcomatoid carcinoma (SCA) is a rare and aggressive malignancy characterized by the coexistence of epithelial and mesenchymal components. While it has been described in various organs, SCA of the ileum is exceptionally rare, with only handful of cases reported in the literature to date. We report a case of a 38-year-old woman presenting with primary subfertility and episodic lower abdominal pain, initially attributed to possible adenomyosis. During subfertility evaluation with a laparoscopic dye test, an incidental polypoidal growth was detected in the distal ileum. Contrast-enhanced computed tomography (CECT) revealed a heterogeneously enhancing mass in the right iliac fossa, suspected to be a gastrointestinal stromal tumor (GIST). Following multidisciplinary team discussions, surgical excision was performed with a laparoscopic assisted right hemicolectomy. Histopathological analysis confirmed a biphasic tumor with carcinomatous and sarcomatous components, consistent with SCA. Evaluation with immunohistochemical markers further narrowed down differential diagnoses. Postoperatively, the patient developed metastatic progression, as evidenced by peritoneal masses and an abdominal wall deposit on repeat CECT. She subsequently underwent adjuvant chemotherapy. SCA of the ileum poses significant diagnostic challenges due to nonspecific clinical features and its rarity. This case underscores the diagnostic complexities and therapeutic challenges of ileal SCA. Collaborative research is essential to develop effective treatment strategies for this rare malignancy.

The mutational landscape and its longitudinal dynamics in relapsed and refractory classic Hodgkin lymphoma

In classic Hodgkin-lymphoma (cHL), only a few cases recur, and only a limited fraction of patients is primary-refractory to standard-polychemotherapy. Underlying genomic features of unfavorable clinical courses remain sparsely characterized. Here, we investigated the genomic characteristics of primary-refractory/relapsed cHL in contrast with responders. Therefore, ultra-deep next-generation panel-sequencing was performed on a total of 59 FFPE-samples (20 responders, 26 relapsed (rHL: 11 initial-diagnosis, 15 relapse) and 13 primary-refractory (prHL: 8 initial-diagnosis, 5 progression) from 44 cHL-patients applying a hybrid-capture approach. We compared samples associated with distinct disease courses concerning their oncogenic drivers, mutational signatures, and perturbed pathways. Compared to responders, mutations in genes such as PMS2, PDGFRB, KAT6A, EPHB1, and HGF were detected more frequently in prHL/rHL. Additionally, we observed that in rHL or prHL, BARD1-mutations occur, whereas ETV1, NF1, and MET-mutations were eliminated through clonal selection. A significant enrichment of non-synonymous variants was detected in prHL compared to responders and a significant selection process in favor of NOTCH-pathway mutations driving rHL or prHL was observed. However, our analysis revealed a negative selection process for non-synonymous variants affecting the hippo-pathway. This study delineates distinct mutational signatures between responders and rHL/prHL, whilst illustrating longitudinal dynamics in mutational profiles using paired samples. Further, several exploitable therapeutic vulnerabilities for rHL and prHL were identified.

Accumulating Genetic Mutations from Primary to Secondary Biliary Tract Cancers: Analysis of Four Patients With Metachronous Biliary Tract Cancer Using Comprehensive Genomic Profiling

BACKGROUND/AIM

Metachronous biliary tract cancer (BTC) is a rare occurrence after curative resection of primary BTC. The genetic alterations and pathogenesis associated with metachronous BTC remain poorly understood.

PATIENTS AND METHODS

We analyzed four patients with metachronous BTC who underwent resection at the Nagoya University Hospital between 2010 and 2024. Gene panel examination was performed on both primary and secondary tumors using next-generation sequencing.

RESULTS

The median interval between resection of the primary tumor and diagnosis of metachronous BTC was 24 months. Genetic alterations were observed in all paired primary and metachronous carcinomas. The number of genetic mutations was higher in metachronous lesions than in primary lesions. CDKN2A and SMAD4 were the most frequently mutated genes in all metachronous lesions. Common genetic mutations between primary and metachronous lesions were confirmed in all four cases, suggesting a common clonal origin.

CONCLUSION

This study demonstrated that characteristic genetic alterations and their accumulation play important roles in metachronous BTC. This suggests that the increasing burden of gene mutations may play a crucial role in the carcinogenesis of metachronous BTC. Further investigation is required to validate these findings and elucidate the underlying molecular mechanisms.

Advances in reversible covalent kinase inhibitors

Reversible covalent kinase inhibitors (RCKIs) are a class of novel kinase inhibitors attracting increasing attention because they simultaneously show the selectivity of covalent kinase inhibitors yet avoid permanent protein-modification-induced adverse effects. Over the last decade, RCKIs have been reported to target different kinases, including Atypical group of kinases. Currently, three RCKIs are undergoing clinical trials. Here, advances in RCKIs are reviewed to systematically summarize the characteristics of electrophilic groups, chemical scaffolds, nucleophilic residues, and binding modes. In so doing, we integrate key insights into privileged electrophiles, the distribution of nucleophiles, and hence effective design strategies for the development of RCKIs. Finally, we provide a further perspective on future design strategies for RCKIs, including those that target proteins other than kinases.

iSoMAs: Finding isoform expression and somatic mutation associations in human cancers

Aberrant alternative splicing, prevalent in cancer, impacts various cancer hallmarks involving proliferation, angiogenesis, and invasion. Splicing disruption often results from somatic point mutations rewiring functional pathways to support cancer cell survival. We introduce iSoMAs (iSoform expression and somatic Mutation Association), an efficient computational pipeline leveraging principal component analysis technique, to explore how somatic mutations influence transcriptome-wide gene expression at the isoform level. Applying iSoMAs to 33 cancer types comprising 9,738 tumor samples in The Cancer Genome Atlas, we identified 908 somatically mutated genes significantly associated with altered isoform expression across three or more cancer types. Mutations linked to differential isoform expression occurred through both cis- and trans-acting mechanisms, involving well-known oncogenes/suppressor genes, RNA binding protein and splicing factor genes. With wet-lab experiments, we verified direct association between TP53 mutations and differential isoform expression in cell cycle genes. Additional iSoMAs genes have been validated in the literature with independent cohorts and/or methods. Despite the complexity of cancer, iSoMAs attains computational efficiency via dimension reduction strategy and reveals critical associations between regulatory factors and transcriptional landscapes.

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

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

The MEK inhibitor trametinib is effective in inhibiting the growth of canine oral squamous cell carcinoma

Oral tumors are relatively common in dogs, and canine oral squamous cell carcinoma (COSCC) is the most prevalent oral malignancy of epithelial origin. COSCC is locally aggressive with up to 20% of patients showing regional or distant metastasis at the time of diagnosis. The treatment of choice most typically involves wide surgical excision. Although long-term remission is possible, treatments are associated with considerable morbidity and can negatively impact functionality and quality of life. OSCCs have substantial upregulation of the RAS-RAF-MEK-MAPK signaling axis, and we had previously hypothesized that small-molecule inhibitors that target RAS signaling might effectively inhibit tumor growth and progression. Here, we demonstrate that the MEK inhibitor trametinib, an FDA-approved drug for human cancers, substantially inhibits the growth of six COSCC cell lines established from current patient tumor samples. We further show preliminary clinical evidence that the drug is able to cause ~ 40% and ~ 80% tumor regression in two out of four patients with spontaneously occurring COSCC, a partial response according to commonly used RECIST criteria. Given the limited treatment options available and the number of dogs for which standard of care is not acceptable, these preliminary findings provide new hope that more suitable treatment options may soon enter the veterinary clinic.

Tumor-Agnostic Therapies in Practice: Challenges, Innovations, and Future Perspectives

This review comprehensively analyzes the current landscape of tumor-agnostic therapies in oncology. Tumor-agnostic therapies are designed to target specific molecular alterations rather than the primary site of the tumor, representing a shift in cancer treatment. We discuss recent approvals by regulatory agencies such as the FDA and EMA, highlighting therapies that have demonstrated efficacy across multiple cancer types sharing common alterations. We delve into the trial methodologies that underpin these approvals, emphasizing innovative designs such as basket trials and umbrella trials. These methodologies present unique advantages, including increased efficiency in patient recruitment and the ability to assess drug efficacy in diverse populations rapidly. However, they also entail certain challenges, including the need for robust biomarkers and the complexities of regulatory requirements. Moreover, we examine the promising prospects for developing therapies for rare cancers that exhibit common molecular targets typically associated with more prevalent malignancies. By synthesizing these insights, this review underscores the transformative potential of tumor-agnostic therapies in oncology. It offers a pathway for personalized cancer treatment that transcends conventional histology-based classification.

MET variants with activating N-lobe mutations identified in hereditary papillary renal cell carcinomas still require ligand stimulation

In hereditary papillary renal cell carcinoma (HPRCC), the hepatocyte growth factor receptor (MET) receptor tyrosine kinase (RTK) mutations recorded to date are located in the kinase domain and lead to constitutive MET activation. This contrasts with MET mutations identified in non-small cell lung cancer (NSCLC), which lead to exon 14 skipping and deletion of a regulatory domain: in this latter case, the mutated receptor still requires ligand stimulation. Sequencing of MET in samples from 158 HPRCC and 2808 NSCLC patients revealed ten uncharacterized mutations. Four of these, all found in HPRCC and leading to amino acid substitutions in the N-lobe of the MET kinase, proved able to induce cell transformation, which was further enhanced by hepatocyte growth factor (HGF) stimulation: His1086Leu, Ile1102Thr, Leu1130Ser and Cis1125Gly. Similar to the variant resulting in MET exon 14 skipping, the two N-lobe MET variants His1086Leu and Ile1102Thr were found to require stimulation by HGF in order to strongly activate downstream signaling pathways and epithelial cell motility. The Ile1102Thr mutation also displayed transforming potential, promoting tumor growth in a xenograft model. In addition, the N-lobe-mutated MET variants were found to trigger a common HGF-stimulation-dependent transcriptional program, consistent with an observed increase in cell motility and invasion. Altogether, this functional characterization revealed that N-lobe variants still require ligand stimulation, in contrast to other RTK variants. This suggests that HGF expression in the tumor microenvironment is important for tumor growth. The sensitivity of these variants to MET inhibitors opens the way for use of targeted therapies for patients harboring the corresponding mutations.

Mechanisms and Strategies to Overcome Drug Resistance in Colorectal Cancer

Colorectal cancer (CRC) is a major cause of cancer-related mortality worldwide, with a significant impact on public health. Current treatment options include surgery, chemotherapy, radiotherapy, molecular-targeted therapy, and immunotherapy. Despite advancements in these therapeutic modalities, resistance remains a significant challenge, often leading to treatment failure, poor progression-free survival, and cancer recurrence. Mechanisms of resistance in CRC are multifaceted, involving genetic mutations, epigenetic alterations, tumor heterogeneity, and the tumor microenvironment. Understanding these mechanisms at the molecular level is crucial for identifying novel therapeutic targets and developing strategies to overcome resistance. This review provides an overview of the diverse mechanisms driving drug resistance in sporadic CRC and discusses strategies currently under investigation to counteract this resistance. Several promising strategies are being explored, including targeting drug transport, key signaling pathways, DNA damage response, cell death pathways, epigenetic modifications, cancer stem cells, and the tumor microenvironment. The integration of emerging therapeutic approaches that target resistance mechanisms aims to enhance the efficacy of current CRC treatments and improve patient outcomes.

Advances in microfluidic platforms for tumor cell phenotyping: from bench to bedside

Heterogeneities among tumor cells significantly contribute towards cancer progression and therapeutic inefficiency. Hence, understanding the nature of cancer through liquid biopsies and isolation of circulating tumor cells (CTCs) has gained considerable interest over the years. Microfluidics has emerged as one of the most popular platforms for performing liquid biopsy applications. Various label-free and labeling techniques using microfluidic platforms have been developed, the majority of which focus on CTC isolation from normal blood cells. However, sorting and profiling of various cell phenotypes present amongst those CTCs is equally important for prognostics and development of personalized therapies. In this review, firstly, we discuss the biophysical and biochemical heterogeneities associated with tumor cells and CTCs which contribute to cancer progression. Moreover, we discuss the recently developed microfluidic platforms for sorting and profiling of tumor cells and CTCs. These techniques are broadly classified into biophysical and biochemical phenotyping methods. Biophysical methods are further classified into mechanical and electrical phenotyping. While biochemical techniques have been categorized into surface antigen expressions, metabolism, and chemotaxis-based phenotyping methods. We also shed light on clinical studies performed with these platforms over the years and conclude with an outlook for the future development in this field.

MET variants with activating N-lobe mutations identified in hereditary papillary renal cell carcinomas still require ligand stimulation

In hereditary papillary renal cell carcinoma (HPRCC), the hepatocyte growth factor receptor (MET) receptor tyrosine kinase (RTK) mutations recorded to date are located in the kinase domain and lead to constitutive MET activation. This contrasts with MET mutations identified in non-small-cell lung cancer (NSCLC), which lead to exon 14 skipping and deletion of a regulatory domain: In this latter case, the mutated receptor still requires ligand stimulation. Sequencing of MET in samples from 158 HPRCC and 2808 NSCLC patients revealed 10 uncharacterized mutations. Four of these, all found in HPRCC and leading to amino acid substitutions in the N-lobe of the MET kinase, proved able to induce cell transformation, which was further enhanced by hepatocyte growth factor (HGF) stimulation: His1086Leu, Ile1102Thr, Leu1130Ser, and Cis1125Gly. Similar to the variant resulting in MET exon 14 skipping, the two N-lobe MET variants His1086Leu and Ile1102Thr were found to require stimulation by HGF in order to strongly activate downstream signaling pathways and epithelial cell motility. The Ile1102Thr mutation also displayed transforming potential, promoting tumor growth in a xenograft model. In addition, the N-lobe-mutated MET variants were found to trigger a common HGF-stimulation-dependent transcriptional program, consistent with an observed increase in cell motility and invasion. Altogether, this functional characterization revealed that N-lobe variants still require ligand stimulation, in contrast to other RTK variants. This suggests that HGF expression in the tumor microenvironment is important for tumor growth. The sensitivity of these variants to MET inhibitors opens the way for use of targeted therapies for patients harboring the corresponding mutations.

Exploring the role of epigenetic regulation in cancer prognosis with epigenetic score

Background

The mechanisms of epigenetic regulation emerge as a fundamental determinant in the complex landscape of cancer initiation and advancement. However, the specific impact of epigenetic regulation on cancer progression remains unclear. To explore the relationship between epigenetic regulation and cancer progression, we utilized transcriptomic data from The Cancer Genome Atlas (TCGA) datasets to investigate the association.

Methods

We obtained transcriptomic data of epigenetic gene dataset from the TCGA database and calculated an epigenetic score using the Least Absolute Shrinkage and Selection Operator (LASSO) Cox model. Additionally, we created a nomogram that integrates the epigenetic score and clinical features, providing a more comprehensive tool for tumor patients prognosis assessment.

Results

We calculated the epigenetic score based on the expression levels of epigenetic-related genes. The nomogram we developed incorporates the epigenetic score and clinical characteristics. The epigenetic score was positively correlated with the expression of genes related to hallmarkers of cancer, including glycolysis, epithelial-mesenchymal transition (EMT), cell cycle, DNA repair, angiogenesis, and inflammatory response. Furthermore, we performed gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analysis to explore the signaling pathways and biological processes in high epigenetic score group.

Conclusion

The epigenetic scoring system developed in this investigation represents an innovative approach that demonstrates remarkable potential in forecasting survival trajectories across diverse cancer types. These groundbreaking insights not only illuminate the intricate interactions between epigenetic mechanisms and gene expression regulation in oncological contexts, but also indicate that the derived epigenetic metric could potentially emerge as a significant prognostic biomarker for cancer outcomes.

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

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

Characterization of RNF144B and PPP2R2A identified by a novel approach using TCGA data in ovarian cancer

TCGA has identified predominant somatic copy number alterations (SCNA) affecting numerous genes in HGSOC. To identify cancer-driver genes from the regions of SCNA, we have devised a scoring system that integrates information from different genetic alterations. Applying this scoring system to the TCGA-HGSOC dataset (n = 316) we have identified several well-known and novel putative cancer genes in HGSOC. We functionally validated the roles of two previously unknown genes, RNF144B and PPP2R2A. RNF144B, an E3 ubiquitin-ligase is amplified and overexpressed in 16% of HGSOC (TCGA). Overexpression of RNF144B in ovarian cancer cells increased cell proliferation, colony formation, and migration. RNF144B was significantly overexpressed in 50% of primary tumors from patients with HGSOC compared to the ovary. Further, it had significantly reduced expression in tumors after chemotherapy. PPP2R2A, the regulatory subunit of PP2A is deleted and downregulated in 38% of HGSOCs (TCGA). Overexpression of PPP2R2A inhibited cell proliferation, colony-formation, migration, and invasion in ovarian cancer cells. In OVCAR-5, which expresses low levels of PPP2R2A, Niraparib inhibited cell proliferation. PPP2R2A was not expressed in 72% of HGSOCs. This report demonstrates this approach to identifying genes from the TCGA data. Further experiments are required to conclusively prove the role of these genes in the pathogenesis of ovarian cancer.

Comprehensive pharmacokinetic profiling and molecular docking analysis of natural bioactive compounds targeting oncogenic biomarkers in breast cancer

Breast cancer is one of the leading causes of death in women worldwide, highlighting the crucial need for novel and effective treatments. In this study, we look at the ability of four natural compounds i.e. Berberine, Curcumin, Withaferin A, and Ellagic Acid to target important breast cancer biomarkers such as B-cell lymphoma 2 (BCL-2), programmed death-ligand 1 (PDL-1), cyclin-dependent kinase 4/6 (CDK4/6) and fibroblast growth factor receptor (FGFR). These indicators have important roles in tumor development, survival, immune response, and cell cycle control, making them potential targets for future cancer treatments. Our study employs a variety of techniques, including pharmacokinetic profiling (ADME), molecular docking, and molecular dynamics simulations, to determine how successful these drugs could be in therapy. The pharmacokinetic investigation found that Berberine and Ellagic Acid stand out due to their high absorption and solubility, implying that they could be suitable for clinical application. When we ran docking simulations, we discovered substantial connections between these chemicals and the target proteins. Additionally, Berberine has a binding affinity of - 9.3 kcal/mol for BCL-2, indicating that it can impair the protein's cancer cell-protective activities. Ellagic Acid, on the other hand, has an even higher binding affinity for PDL-1 of - 9.8 kcal/mol, showing that it may be able to increase immune responses against tumors. Molecular dynamics simulations over 100 ns demonstrated the stability of these protein-ligand complexes. Interestingly, Ellagic Acid was found to be more structurally stable than Berberine throughout these simulations. We found consistent interactions between the chemicals and key residues in the target proteins. For example, Ellagic Acid (CID: 5281855) established persistent linkages with LYS43, ASP163, and VAL27, whereas Berberine (CID: 2353) interacted with VAL27, ALA41, and LEU152 throughout the simulation. In conclusion, the combination of good pharmacokinetics, robust interactions with cancer biomarkers, and stable complexes makes Berberine and Ellagic Acid interesting candidates for further investigation as natural inhibitors in breast cancer treatment. These findings establish the framework for future research into novel and inventive techniques to effectively combating breast cancer.

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

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

The Role of p53 Mutations in Early and Late Response to Mitotic Aberrations

Mutations in the TP53 gene and chromosomal instability (CIN) are two of the most common alterations in cancer. CIN, marked by changes in chromosome numbers and structure, drives tumor development, but is poorly tolerated in healthy cells, where developmental and tissue homeostasis mechanisms typically eliminate cells with chromosomal abnormalities. Mechanisms that allow cancer cells to acquire and adapt to CIN remain largely unknown. Tumor suppressor protein p53, often referred to as the "guardian of the genome", plays a critical role in maintaining genomic stability. In cancer, CIN strongly correlates with TP53 mutations, and recent studies suggest that p53 prevents the propagation of cells with abnormal karyotypes arising from mitotic errors. Furthermore, p53 dysfunction is frequent in cells that underwent whole-genome doubling (WGD), a process that facilitates CIN onset, promotes aneuploidy tolerance, and is associated with poor patient prognosis across multiple cancer types. This review summarizes current insights into p53's role in protecting cells from chromosome copy number alterations and discusses the implications of its dysfunction for the adaption and propagation of cancer cells.

Genetic advancements in breast cancer treatment: a review

Breast cancer (BC) remains a leading cause of cancer-related deaths among women globally, highlighting the urgent need for more effective and targeted therapies. Traditional treatments, including surgery, chemotherapy, and radiation, face limitations such as drug resistance, metastasis, and severe side effects. Recent advancements in gene therapy, particularly CRISPR/Cas9 technology and Oncolytic Virotherapy (OVT), are transforming the BC treatment landscape. CRISPR/Cas9 enables precise gene editing to correct mutations in oncogenes like HER2 and MYC, directly addressing tumor growth and immune evasion. Simultaneously, OVT leverages genetically engineered viruses to selectively destroy cancer cells and stimulate robust antitumor immune responses. Despite their potential, gene therapies face challenges, including off-target effects, delivery issues, and ethical concerns. Innovations in delivery systems, combination strategies, and integrating gene therapy with existing treatments offer promising solutions to overcome these barriers. Personalized medicine, guided by genomic profiling, further enhances treatment precision by identifying patient-specific mutations, such as BRCA1 and BRCA2, allowing for more tailored and effective interventions. As research progresses, the constructive interaction between gene therapy, immunotherapy, and traditional approaches is paving the way for groundbreaking advancements in BC care. Continued collaboration between researchers and clinicians is essential to translate these innovations into clinical practice, ultimately improving BC patients' survival rates and quality of life.

Image Analysis as tool for Predicting Colorectal Cancer Molecular Alterations: A Scoping Review

Objectives

Among the most important diagnostic indicators of colorectal cancer; however, measuring molecular alterations are invasive and expensive. This study aimed to investigate the application of image processing to predict molecular alterations in colorectal cancer.

Methods

In this scoping review, we searched for relevant literature by searching the Web of Science, Scopus, and PubMed databases. The method of selecting the articles and reporting the findings was according to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses; moreover, the Strengthening the Reporting of Observational Studies in Epidemiology checklist was used to assess the quality of the studies.

Results

Sixty seven out of 2,223 articles, 67 were relevant to the aim of the study, and finally 41 studies with sufficient quality were reviewed. The prediction of Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS), Neuroblastoma RAS Viral (NRAS), B-Raf proto-oncogene, serine/threonine kinase (BRAF), Tumor Protein 53 (TP53), Adenomatous Polyposis Coli, and microsatellite instability (MSI) with the help of image analysis has received more attention than other molecular characteristics. The studies used computed tomography (CT), magnetic resonance imaging (MRI), and 18F-FDG positron emission tomography (PET)/CT with radionics and quantitative analysis to predict molecular alterations in colorectal cancer, analyzing features like texture, maximum standard uptake value, and MTV using various statistical methods. In 39 studies, there was a significant relationship between the features extracted from these images and molecular alterations. Different modalities were used to measure the area under the receiver operating characteristic curve for predicting the alterations in KRAS, MSI, BRAF, and TP53, with an average of 78, 81, 80 and 71%, respectively.

Conclusion

This scoping review underscores the potential of radiogenomics in predicting molecular alterations in colorectal cancer through non-invasive imaging modalities, like CT, MRI, and 18F-FDG PET/CT. The analysis of 41 studies showed the appropriate prediction of key alterations, such as KRAS, NRAS, BRAF, TP53, and MSI, highlighting the promise of radionics and texture features in enhancing predictive accuracy.

Pan-cancer analysis of biallelic inactivation in tumor suppressor genes identifies KEAP1 zygosity as a predictive biomarker in lung cancer

The canonical model of tumor suppressor gene (TSG)-mediated oncogenesis posits that loss of both alleles is necessary for inactivation. Here, through allele-specific analysis of sequencing data from 48,179 cancer patients, we define the prevalence, selective pressure for, and functional consequences of biallelic inactivation across TSGs. TSGs largely assort into distinct classes associated with either pan-cancer (Class 1) or lineage-specific (Class 2) patterns of selection for biallelic loss, although some TSGs are predominantly monoallelically inactivated (Class 3/4). We demonstrate that selection for biallelic inactivation can be utilized to identify driver genes in non-canonical contexts, including among variants of unknown significance (VUSs) of several TSGs such as KEAP1. Genomic, functional, and clinical data collectively indicate that KEAP1 VUSs phenocopy established KEAP1 oncogenic alleles and that zygosity, rather than variant classification, is predictive of therapeutic response. TSG zygosity is therefore a fundamental determinant of disease etiology and therapeutic sensitivity.

Circulating microRNA panels for multi-cancer detection and gastric cancer screening: leveraging a network biology approach

BACKGROUND

Screening tests, particularly liquid biopsy with circulating miRNAs, hold significant potential for non-invasive cancer detection before symptoms manifest.

METHODS

This study aimed to identify biomarkers with high sensitivity and specificity for multiple and specific cancer screening. 972 Serum miRNA profiles were compared across thirteen cancer types and healthy individuals using weighted miRNA co-expression network analysis. To prioritize miRNAs, module membership measure and miRNA trait significance were employed. Subsequently, for specific cancer screening, gastric cancer was focused on, using a similar strategy and a further step of preservation analysis. Machine learning techniques were then applied to evaluate two distinct miRNA panels: one for multi-cancer screening and another for gastric cancer classification.

RESULTS

The first panel (hsa-miR-8073, hsa-miR-614, hsa-miR-548ah-5p, hsa-miR-1258) achieved 96.1% accuracy, 96% specificity, and 98.6% sensitivity in multi-cancer screening. The second panel (hsa-miR-1228-5p, hsa-miR-1343-3p, hsa-miR-6765-5p, hsa-miR-6787-5p) showed promise in detecting gastric cancer with 87% accuracy, 90% specificity, and 89% sensitivity.

CONCLUSIONS

Both panels exhibit potential for patient classification in diagnostic and prognostic applications, highlighting the significance of liquid biopsy in advancing cancer screening methodologies.

A New Blood-Based Epigenetic Diagnostic Biomarker Test (EpiSwitch®® NST) with High Sensitivity and Positive Predictive Value for Colorectal Cancer and Precancerous Polyps

BACKGROUND/OBJECTIVES

Colorectal cancer (CRC) arises from the epithelial lining of the colon or rectum, often following a progression from benign adenomatous polyps to malignant carcinoma. Screening modalities such as colonoscopy, faecal immunochemical tests (FIT), and FIT-DNA are critical for early detection and prevention, but non-invasive methods lack sensitivity to polyps and early CRC. Chromosome conformations (CCs) are potent epigenetic regulators of gene expression. We have previously developed an epigenetic assay, EpiSwitch®®, that employs an algorithmic-based CCs analysis. Using EpiSwitch®® technology, we have shown the presence of cancer-specific CCs in peripheral blood mononuclear cells (PBMCs) and primary tumours of patients with melanoma and prostate cancer. EpiSwitch®®-based commercial tests are now available to diagnose prostate cancer with 94% accuracy (PSE test) and response to immune checkpoint inhibitors across 14 cancers with 85% accuracy (CiRT test). Methods/Results/Conclusions: Using blood samples collected from n = 171 patients with CRC, n = 44 patients with colorectal polyps and n = 110 patients with a 'clear' colonoscopy we performed whole Genome DNA screening for CCs correlating to CRC diagnosis. Our findings suggest the presence of two eight-marker CC signatures (EpiSwitch®® NST) in whole blood that allow diagnosis of CRC and precancerous polyps, respectively. Independent validation cohort testing demonstrated high accuracy in identifying colorectal polyps and early versus late stages of CRC with an exceptionally high sensitivity of 79-90% and a high positive prediction value of 60-84%. Linking the top diagnostic CCs to nearby genes, we have built pathways maps that likely underline processes contributing to the pathology of polyp and CRC progression, including TGFβ, cMYC, Rho GTPase, ROS, TNFa/NFκB, and APC.

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

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

Personalized prediction of anticancer potential of non-oncology drugs through learning from genome derived molecular pathways

Advances in cancer genomics have significantly expanded our understanding of cancer biology. However, the high cost of drug development limits our ability to translate this knowledge into precise treatments. Approved non-oncology drugs, comprising a large repository of chemical entities, offer a promising avenue for repurposing in cancer therapy. Herein we present CHANCE, a supervised machine learning model designed to predict the anticancer activities of non-oncology drugs for specific patients by simultaneously considering personalized coding and non-coding mutations. Utilizing protein-protein interaction networks, CHANCE harmonizes multilevel mutation annotations and integrates pharmacological information across different drugs into a single model. We systematically benchmarked the performance of CHANCE and show its predictions are better than previous model and highly interpretable. Applying CHANCE to approximately 5000 cancer samples indicated that >30% might respond to at least one non-oncology drug, with 11% non-oncology drugs predicted to have anticancer activities. Moreover, CHANCE predictions suggested an association between SMAD7 mutations and aspirin treatment response. Experimental validation using tumor cells derived from seven patients with pancreatic or esophageal cancer confirmed the potential anticancer activity of at least one non-oncology drug for five of these patients. To summarize, CHANCE offers a personalized and interpretable approach, serving as a valuable tool for mining non-oncology drugs in the precision oncology era.

Understanding developing kidneys and Wilms tumors one cell at a time

Single-cell sequencing-based techniques are revolutionizing all fields of biomedical sciences, including normal kidney development and how this is disturbed in the development of Wilms tumor. The many different techniques and the differences between them can obscure which technique is best used to answer which question. In this review we summarize the techniques currently available, discuss which have been used in kidney development or Wilms tumor context, and which techniques can or should be combined to maximize the increase in biological understanding we can get from them.

Tumor-derived exosomes induce neutrophil infiltration and reprogramming to promote T-cell exhaustion in hepatocellular carcinoma

Rationale: High neutrophil infiltration in hepatocellular carcinoma (HCC) is associated with a poor prognosis in patients with HCC. Tumor-derived exosomes (TDEs) have been proven to be important in the reprogramming of tumor-associated neutrophils (TANs), but the roles and mechanisms have not been fully clarified. Methods: The roles of HCC-exosome-reprogrammed neutrophils on tumor progression were evaluated in the DEN/CCl4-induced HCC mouse model by blocking neutrophil infiltration, depleting neutrophil, and neutrophil adoptive transfer. Transcriptome sequencing and flow cytometry were performed to investigate the effects of HCC exosomes on the phenotype and function of neutrophils. The mobilization and apoptosis of neutrophils were evaluated by the Transwell experiment and Annexin V/7-AAD staining, respectively. Moreover, we detected the effects of HCC-exosome-reprogrammed neutrophils on T cells by flow cytometry. Next, we used the NF-κB pathway inhibitor JSH-23 and miR-362-5p inhibitor or mimic to determine the molecular mechanisms. Lastly, we constructed the miR-362-5p sponge to validate its targeted therapeutic potential. Results: We found that HCC exosomes induced neutrophil infiltration and T-cell exhaustion in the livers of DEN/CCl4-induced HCC mice and promoted tumor progression. Blocking neutrophil infiltration and depleting neutrophils diminished these promotive effects of HCC exosomes. In addition, HCC exosome-reprogrammed neutrophils display proinflammatory and protumor phenotypes, and can directly induce T-cell exhaustion in vitro. The transfer of HCC exosome-reprogrammed neutrophils exacerbated tumor progression and induced T-cell exhaustion, as evidenced by the downregulation of IFN-γ and TNF-α, and the upregulation of PD-1 and Tim3 in T cells. Mechanistically, we found that HCC exosomes upregulate the expression of miR-362-5p in neutrophils and activate the NF-κB signaling pathway by targeting CYLD, promoting the survival and recruitment of neutrophils. In HCC mice, blocking miR-362-5p suppressed neutrophil infiltration, attenuated T-cell exhaustion, and suppressed HCC progression. Conclusions: This study clarified the roles of HCC exosomes on neutrophil infiltration and reprogramming and identified a potential target miR-362-5p for HCC treatment.

CAR-T cell therapy for breast cancer: Current status and future perspective

Within the expanding therapeutic landscape for breast cancer (BC), metastatic breast cancer (MBC) remains virtually incurable and tend to develop resistance to conventional treatments ultimately leading to metastatic progression and death. Cellular immunotherapy (CI), particularly chimeric antigen receptor-engineered T (CAR-T) cells, has emerged as a promising approach for addressing this challenge. In the wake of their striking efficacy against hematological cancers, CAR-T cells have also been used where the clinical need is greatest - in patients with aggressive BCs. Unfortunately, current outcomes fall considerably short of replicating that success, primarily owing to the scarcity of tumor-specific antigens and the immunosuppressive microenvironment within BC. Herein, we provide an up-to-date overview of both preclinical and clinical data concerning the application of CAR-T cell therapy in BC. By surveying the existing literature, we discuss the prevailing constrains of this therapeutic approach and overview possible strategies to advance it in the context of breast malignancies. Possible approaches include employing synthetic biology to refine antigen targeting and mitigate off-target toxicity, utilizing logic-gated CAR constructs to enhance specificity, and leveraging armored CARs to remodel the tumor micro-environment. Temporal and spatial regulation of CAR-T cells using inducible gene switches and external triggers further improves safety and functionality. In addition, promoting T cell homing through chemokine receptor engineering and enhancing manufacturing processes with universal CAR platforms expand therapeutic applicability. These innovations not only address antigen escape and T cell exhaustion but also optimize the efficacy and safety profile of CAR-T cell therapy. We, therefore, outline a trajectory wherein CAR-T cells may evolve from a promising experimental approach to a standard modality in BC therapy.

Potential promising of synthetic lethality in cancer research and treatment

Cancer is a complex disease driven by multiple genetic changes, including mutations in oncogenes, tumor suppressor genes, DNA repair genes, and genes involved in cancer metabolism. Synthetic lethality (SL) is a promising approach in cancer research and treatment, where the simultaneous dysfunction of specific genes or pathways causes cell death. By targeting vulnerabilities created by these dysfunctions, SL therapies selectively kill cancer cells while sparing normal cells. SL therapies, such as PARP inhibitors, WEE1 inhibitors, ATR and ATM inhibitors, and DNA-PK inhibitors, offer a distinct approach to cancer treatment compared to conventional targeted therapies. Instead of directly inhibiting specific molecules or pathways, SL therapies exploit genetic or molecular vulnerabilities in cancer cells to induce selective cell death, offering benefits such as targeted therapy, enhanced treatment efficacy, and minimized harm to healthy tissues. SL therapies can be personalized based on each patient's unique genetic profile and combined with other treatment modalities to potentially achieve synergistic effects. They also broaden the effectiveness of treatment across different cancer types, potentially overcoming drug resistance and improving patient outcomes. This review offers an overview of the current understanding of SL mechanisms, advancements, and challenges, as well as the preclinical and clinical development of SL. It also discusses new directions and opportunities for utilizing SL in targeted therapy for anticancer treatment.

The "Ins and Outs and What-Abouts" of H2A.Z: A tribute to C. David Allis

In 2023, the brilliant chromatin biologist C. David Allis passed away leaving a large void in the scientific community and broken hearts in his family and friends. With this review, we want to tribute Dave's enduring inspiration by focusing on the histone variant H2A.Z, a nucleosome component he was the first to discover as hv1 in Tetrahymena. We summarize the latest findings from the past 5 years regarding the mammalian H2A.Z histone, focusing on its deposition and eviction mechanisms, its roles in transcriptional regulation, DNA damage repair, chromatin structure organization, and embryonic development, as well as how its deregulation or mutation(s) of its histone chaperones contribute to disease development. As Dave liked to say 'Every amino acid matters'; the discovery and characterization of functionally different H2A.Z's isoforms, which vary only in three amino acids, prove him-once again-right.

Mutational and co-mutational landscape of early onset colorectal cancer

INTRODUCTION

Colorectal cancer (CRC) incidence and mortality before 50 have been rising alarmingly in the recent decades.

METHODS

Using a cohort of 10,000 patients, this study investigates the clinical, mutational, and co-mutational features of CRC in early-onset (EOCRC, < 50 years) compared to late-onset (LOCRC, ≥ 50 years).

RESULTS

EOCRC was associated with a higher prevalence of Asian and Hispanic patients, rectal or left-sided tumors (72% vs. 59%), and advanced-stage disease. Molecular analyses revealed differences in mutation patterns, with EOCRC having higher frequencies of TP53 (74% vs. 68%, p < 0.01) and SMAD4 (17% vs. 14%, p = 0.015), while BRAF (5% vs. 11%, p < 0.001) and NOTCH1 (2.7% vs. 4.1%, p = 0.01) mutations were more prevalent in LOCRC. Stratification by tumor site and MSI status highlighted significant location- and age-specific molecular differences, such as increased KRAS and CTNNB1 mutations in right-sided EOCRC and higher BRAF prevalence in MSI-H LOCRC (47% vs. 6.7%, p < 0.001). Additionally, co-occurrence analysis revealed unique mutational networks in EOCRC MSS, including significant co-occurrences of FBXW7 with NOTCH3, RB1, and PIK3R1.

CONCLUSION

This study highlights the significance of age-specific molecular profiling, offering insights into the unique biology of EOCRC and potential clinical applications.

Positive Selection Shapes Breast Cancer Tumor Suppressor Genes: Unveiling Insights into BRCA1, BRCA2, and MDC1 Stability

Worldwide, breast cancer is the leading cause of death in women with cancers. Given this situation, new approaches to treatment are urgently needed. Tumor Suppressor Genes (TSGs) defects play a crucial role in tumor development, and recent studies propose their reactivation as a promising way for clinical intervention in breast cancer. Here, we performed detailed evolutionary analyses of 241 breast cancer TSGs across 25 mammalian genomes, revealing 28 genes under strong positive selection. These genes exhibit elevated molecular pressure in codons corresponding to amino acids located in crucial protein domains and motifs. Notably, one positively selected site in the BRCA1 C-terminal domain is known for its role in DNA damage response, suggesting potential interference with DNA repair mechanisms. Moreover, the substitution of some other sites found in important key motifs, namely two codons in BRCA2 (752 and 939) localized within the phosphoinositide-3-OH-kinase-related and playing a crucial role in the DNA repair and the DNA damage checkpoints. Our findings could be inspirational to foster future recommendations for drug-targeting sites and further illuminate the function of these proteins. Finally, the code developed in our study is delivered in the Automated tool for positive selection (ATPs) ( https://github.com/APS-P/Automated-Tool-for-Positive-Selection-ATPS-/wiki ) to assist the easy reproducibility and support future evolutionary genomics analyses.

TP53: the unluckiest of genes?

The transcription factor p53 plays a key role in the cellular defense against cancer development. It is inactivated in virtually every tumor, and in every second tumor this inactivation is due to a mutation in the TP53 gene. In this perspective, we show that this diverse mutational spectrum is unique among all other cancer-associated proteins and discuss what drives the selection of TP53 mutations in cancer. We highlight that several factors conspire to make the p53 protein particularly vulnerable to inactivation by the mutations that constantly plague our genome. It appears that the TP53 gene has emerged as a victim of its own evolutionary past that shaped its structure and function towards a pluripotent tumor suppressor, but came with an increased structural fragility of its DNA-binding domain. TP53 loss of function - with associated dominant-negative effects - is the main mechanism that will impair TP53 tumor suppressive function, regardless of whether a neomorphic phenotype is associated with some of these variants.

Role of 3-mercaptopyruvate sulfurtransferase in cancer: Molecular mechanisms and therapeutic perspectives

The occurrence and development of tumor is mediated by a wide range of complex mechanisms. Subsequent to nitric oxide and carbon monoxide, hydrogen sulfide (H2S) holds the distinction of being the third identified gasotransmitter. Alternation of H2S level has been widely demonstrated to induce an array of disturbances in important cancer cell signaling pathways. As a result, the effects of H2S-catalyzing enzymes in cancers also attract widspread attention. 3-mercaptopyruvate sulfurtransferase (3-MST) is privileged to be one of them. In fact, 3-MST is overexpressed in many tumors including human colon cancer, lung adenocarcinoma, and bladder urothelial carcinoma. But it is also lowly expressed in hepatocellular carcinoma. In this review, we focus on the generation of endogenous H2S and polysulfides, facilitated by 3-MST. Additionally, we delve deeply into the potential role of 3-MST in tumorigenesis and development. The impact of 3-MST inhibition on the development of tumors and its potential for tumor therapy are also highlighted.

The dynamics of loss of heterozygosity events in genomes

Genomic instability is a hallmark of tumorigenesis, yet it also plays an essential role in evolution. Large-scale population genomics studies have highlighted the importance of loss of heterozygosity (LOH) events, which have long been overlooked in the context of genetic diversity and instability. Among various types of genomic mutations, LOH events are the most common and affect a larger portion of the genome. They typically arise from recombination-mediated repair of double-strand breaks (DSBs) or from lesions that are processed into DSBs. LOH events are critical drivers of genetic diversity, enabling rapid phenotypic variation and contributing to tumorigenesis. Understanding the accumulation of LOH, along with its underlying mechanisms, distribution, and phenotypic consequences, is therefore crucial. In this review, we explore the spectrum of LOH events, their mechanisms, and their impact on fitness and phenotype, drawing insights from Saccharomyces cerevisiae to cancer. We also emphasize the role of LOH in genomic instability, disease, and genome evolution.

Molecular characteristics, clinical significance and cancer‑immune interactions of pyroptosis‑related genes in colorectal cancer

Colorectal cancer (CRC) is a malignant tumor with poor prognosis. Pyroptosis is a newly discovered type of programmed cell death that is typically accompanied by a strong inflammatory response. Accumulating evidence suggests that pyroptosis-related genes (PRGs) may have important roles in the development of malignant tumors. However, the association between PRG expression and clinical outcomes in CRC remain unclear. In the present study, the genetic variations and transcriptional patterns of 52 PRGs were comprehensively analyzed using cohorts from The Cancer Genome Atlas and Gene Expression Omnibus and the mRNA expression levels of 7 PRGs in collected CRC samples were validated using reverse transcription-quantitative PCR. Using LASSO-Cox analysis, a PRG score was then generated and the relationship between the PRG score and prognosis, immune cell infiltration and drug sensitivity in CRC was uncovered. In the present study, the mutation and expression patterns of PRGs were analyzed and it was found that these genes were differentially expressed in CRC tissues compared with normal tissues. Based on the expression patterns of the PRGs, patients with CRC were divided into two subtypes (cluster A and B), of which cluster B had an improved prognosis and a higher abundance of immune cells. Next, differentially expressed genes between clusters A and B were identified and a PRG risk score closely related to the prognosis of CRC was constructed. Then, a nomogram for evaluating the overall survival of patients was constructed. Furthermore, a low PRG risk score was characterized by immune activation and closely related to the microsatellite instability-high pattern. Additionally, the PRG risk score was notably correlated with drug sensitivity. In conclusion, the mutation and expression characteristics of PRGs in CRC were comprehensively analyzed and a prognostic PRG signature was constructed in the present study. This signature may predict immune cell infiltration and therapeutic response in CRC, providing new insights into the prognosis and treatment of CRC.

Targeting the PD-1/PD-L1 Signaling Pathway for Cancer Therapy: Focus on Biomarkers

The PD1/PD-L1 axis plays an important immunosuppressive role during the T-cell-mediated immune response, which is essential for the physiological homeostasis of the immune system. The biology of the immunological microenvironment is extremely complex and crucial for the development of treatment strategies for immunotherapy. Characterization of the immunological, genomic or transcriptomic landscape of cancer patients could allow discrimination between responders and non-responders to anti-PD-1/PD-L1 therapy. Immune checkpoint inhibitor (ICI) therapy has shown remarkable efficacy in a variety of malignancies in landmark trials and has fundamentally changed cancer therapy. Current research focuses on strategies to maximize patient selection for therapy, clarify mechanisms of resistance, improve existing biomarkers, including PD-L1 expression and tumor mutational burden (TMB), and discover new biomarkers. In this review, we focus on the function of the PD-1/PD-L1 signaling pathway and discuss the immunological, genomic, epigenetic and transcriptomic landscape in cancer patients receiving anti-PD-1/PD-L1 therapy. Finally, we provide an overview of the clinical trials testing the efficacy of antibodies against PD-1/PD-L1.