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Skin cancer comprises one-third of all diagnosed cancer cases and remains a major health concern. Genetic and environmental parameters serve as the two main risk factors associated with the development of skin cancer, with ultraviolet radiation being the most common environmental risk factor. Studies have also found fair complexion, arsenic toxicity, indoor tanning, and family history among the prevailing causes of skin cancer. Prevention and early diagnosis play a crucial role in reducing the frequency and ensuring effective management of skin cancer. Recent studies have focused on exploring minimally invasive or non-invasive diagnostic technologies along with artificial intelligence to facilitate rapid and accurate diagnosis. The treatment of skin cancer ranges from traditional surgical excision to various advanced methods such as phototherapy, radiotherapy, immunotherapy, targeted therapy, and combination therapy. Recent studies have focused on immunotherapy, with the introduction of new checkpoint inhibitors and personalized immunotherapy enhancing treatment efficacy. Advancements in multi-omics, nanotechnology, and artificial intelligence have further deepened the understanding of the mechanisms underlying tumoral growth and their interaction with therapeutic effects, which has paved the way for precision oncology. This review aims to highlight the recent advancements in the understanding and management of skin cancer, and provide an overview of existing and emerging diagnostic, prognostic, and therapeutic modalities, while highlighting areas that require further research to bridge the existing knowledge gaps.
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Melanoma , Neoplasias Cutâneas , Humanos , Neoplasias Cutâneas/diagnóstico , Neoplasias Cutâneas/terapia , Neoplasias Cutâneas/prevenção & controle , Melanoma/diagnóstico , Melanoma/terapia , Melanoma/prevenção & controle , Imunoterapia/métodos , Inteligência ArtificialRESUMO
The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas9 system, a groundbreaking innovation in genetic engineering, has revolutionized our approach to surmounting complex diseases, culminating in CASGEVY™ approved for sickle cell anemia. Derived from a microbial immune defense mechanism, CRISPR/Cas9, characterized as precision, maneuverability and universality in gene editing, has been harnessed as a versatile tool for precisely manipulating DNA in mammals. In the process of applying it to practice, the consecutive exploitation of novel orthologs and variants never ceases. It's conducive to understanding the essentialities of diseases, particularly cancer, which is crucial for diagnosis, prevention, and treatment. CRISPR/Cas9 is used not only to investigate tumorous genes functioning but also to model disparate cancers, providing valuable insights into tumor biology, resistance, and immune evasion. Upon cancer therapy, CRISPR/Cas9 is instrumental in developing individual and precise cancer therapies that can selectively activate or deactivate genes within tumor cells, aiming to cripple tumor growth and invasion and sensitize cancer cells to treatments. Furthermore, it facilitates the development of innovative treatments, enhancing the targeting efficiency of reprogrammed immune cells, exemplified by advancements in CAR-T regimen. Beyond therapy, it is a potent tool for screening susceptible genes, offering the possibility of intervening before the tumor initiative or progresses. However, despite its vast potential, the application of CRISPR/Cas9 in cancer research and therapy is accompanied by significant efficacy, efficiency, technical, and safety considerations. Escalating technology innovations are warranted to address these issues. The CRISPR/Cas9 system is revolutionizing cancer research and treatment, opening up new avenues for advancements in our understanding and management of cancers. The integration of this evolving technology into clinical practice promises a new era of precision oncology, with targeted, personalized, and potentially curative therapies for cancer patients.
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Sistemas CRISPR-Cas , Neoplasias , Medicina de Precisão , Humanos , Sistemas CRISPR-Cas/genética , Medicina de Precisão/métodos , Neoplasias/genética , Neoplasias/terapia , Edição de Genes/métodos , Animais , Oncologia/métodos , Oncologia/tendênciasRESUMO
The liver is a frequent site of metastasis in advanced gastric cancer (GC). Despite significant advancements in diagnostic and therapeutic techniques, the overall survival rate for patients afflicted with gastric cancer liver metastasis (GCLM) remains dismally low. Precision oncology has made significant progress in identifying therapeutic targets and enhancing our understanding of metastasis mechanisms through genome sequencing and molecular characterization. Therefore, it is crucial to have a comprehensive understanding of the various molecular processes involved in GCLM and the fundamental principles of systemic therapy to develop new treatment approaches. This paper aims to review recent findings on the diagnosis, potential biomarkers, and therapies targeting the multiple molecular processes of GCLM, with the goal of improving treatment strategies for patients with GCLM.
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INTRODUCTION: Next-generation sequencing (NGS) identifies genetic variants to inform personalized treatment plans. Insufficient evidence of cost-effectiveness impedes the integration of NGS into routine cancer care. The complexity of personalized treatment challenges conventional economic evaluation. Clearly delineating challenges informs future cost-effectiveness analyses to better value and contextualize health, preference-, and equity-based outcomes. AREAS COVERED: We conducted a scoping review to characterize the applied methods and outcomes of economic evaluations of NGS in oncology and identify existing challenges. We included 27 articles published since 2016 from a search of PubMed, Embase, and Web of Science. Identified challenges included defining the evaluative scope, managing evidentiary limitations including lack of causal evidence, incorporating preference-based utility, and assessing distributional and equity-based impacts. These challenges reflect the difficulty of generating high-quality clinical effectiveness and real-world evidence (RWE) for NGS-guided interventions. EXPERT OPINION: Adapting methodological approaches and developing life-cycle health technology assessment (HTA) guidance using RWE is crucial for implementing NGS in oncology. Healthcare systems, decision-makers, and HTA organizations are facing a pivotal opportunity to adapt to an evolving clinical paradigm and create innovative regulatory and reimbursement processes that will enable more sustainable, equitable, and patient-oriented healthcare.
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(1) Background: Pancreatic ductal adenocarcinoma (PDAC) has low survival rates despite treatment advancements. Aim: This study aims to show how molecular profiling could possibly guide personalized treatment strategies, which may help improve survival outcomes in patients with PDAC. (2) Materials and Methods: A retrospective analysis of 142 PDAC patients from a single academic center was conducted. Patients underwent chemotherapy and next-generation sequencing for molecular profiling. Key oncogenic pathways were identified using the Reactome pathway database. Survival analysis was performed using Kaplan-Meier curves and Cox Proportional Hazards Regression. (3) Results: Patients mainly received FOLFIRINOX (n = 62) or gemcitabine nab-paclitaxel (n = 62) as initial chemotherapy. The median OS was 13.6 months. Longer median OS was noted in patients with NOTCH (15 vs. 12.3 months, p = 0.007) and KIT pathway mutations (21.3 vs. 12.12 months, p = 0.04). Combinatorial pathway analysis indicated potential synergistic effects on survival. In the PFS, PI3K pathway (6.6 vs. 5.7 months, p = 0.03) and KIT pathway (10.3 vs. 6.2 months, p = 0.03) mutations correlated with improved PFS within the gemcitabine nab-paclitaxel subgroup. (4) Conclusions: Molecular profiling could play a role in PDAC for predicting outcomes and responses to therapies like FOLFIRINOX and gemcitabine nab-paclitaxel. Integrating genomic data into clinical decision-making can benefit PDAC treatment, though further validation is needed to fully utilize precision oncology in PDAC management.
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As the projected incidence and mortality of cancer in Sub-Saharan Africa (SSA) rises to epidemic proportions, it is imperative that more is done to identify the genomic differences and commonalities between patients of African and European ancestry to fulfil the promise of precision oncology. Here, we summarize the utility of precision oncology approaches, with a focus on comprehensive genomic profiling (CGP) and consolidate examples of national and international consortia that are driving the field forward. We describe the importance of genomic diversity and its relevance in cancer, and propose recommendations, success factors and desired outcomes for precision oncology consortia to adopt in SSA. Through this, we hope to catalyze the initiation of such projects and to contribute to improving cancer patient outcomes in the region.
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The tumor microenvironment (TME) plays a fundamental role in tumorigenesis, tumor progression, and anti-cancer immunity potential of emerging cancer therapeutics. Understanding inter-patient TME heterogeneity, however, remains a challenge to efficient drug development. This article applies recent advances in machine learning (ML) for survival analysis to a retrospective study of NSCLC patients who received definitive surgical resection and immune pathology following surgery. ML methods are compared for their effectiveness in identifying prognostic subtypes. Six survival models, including Cox regression and five survival machine learning methods, were calibrated and applied to predict survival for NSCLC patients based on PD-L1 expression, CD3 expression, and ten baseline patient characteristics. Prognostic subregions of the biomarker space are delineated for each method using synthetic patient data augmentation and compared between models for overall survival concordance. A total of 423 NSCLC patients (46% female; median age [inter quantile range]: 67 [60-73]) treated with definite surgical resection were included in the study. And 219 (52%) patients experienced events during the observation period consisting of a maximum follow-up of 10 years and median follow up 78 months. The random survival forest (RSF) achieved the highest predictive accuracy, with a C-index of 0.84. The resultant biomarker subtypes demonstrate that patients with high PD-L1 expression combined with low CD3 counts experience higher risk of death within five-years of surgical resection.
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Biomarcadores Tumorais , Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Aprendizado de Máquina , Microambiente Tumoral , Humanos , Carcinoma Pulmonar de Células não Pequenas/patologia , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Carcinoma Pulmonar de Células não Pequenas/cirurgia , Feminino , Masculino , Idoso , Pessoa de Meia-Idade , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/mortalidade , Neoplasias Pulmonares/cirurgia , Prognóstico , Estudos Retrospectivos , Biomarcadores Tumorais/metabolismo , Antígeno B7-H1/metabolismo , Análise de SobrevidaRESUMO
BACKGROUND: TROP2 (TACSTD2) expression is associated with decreased overall survival (OS) in some solid tumors, and the TROP2-targeting antibody-drug conjugate (ADC) sacituzumab govitecan has been approved in breast and urothelial carcinomas. We aimed to explore the multi-omic landscape associated with TACSTD2 gene expression in various solid tumors to identify patients most likely to benefit from this approach. METHODS: Breast (Nâ =â 11 246), colorectal (Nâ =â 15 425), hepatocellular (Nâ =â 433), pancreatic (Nâ =â 5488), and urothelial (Nâ =â 4125) tumors were stratified into quartiles by TACSTD2 gene expression, analyzed by next-generation DNA sequencing, whole transcriptome sequencing, and immunohistochemistry at Caris Life Sciences (Phoenix, AZ). Survival data were obtained from insurance claims, and Kaplan-Meier estimates were calculated for molecularly defined cohorts. RESULTS: Several pathogenic mutations were associated with TACSTD2-high tumors, including TP53 in breast, colorectal (CRC), pancreatic, and hepatocellular cancers; KRAS in pancreatic and CRC cancers; ARID1A and FGFR3 in urothelial cancer; and CTNNB1 in hepatocellular cancer. TACSTD2-low breast tumors were enriched for copy number amplifications in CCND1 and FGF/R family member genes. TACSTD2 high was generally associated with more immune cell infiltration and greater T-cell inflammation scores. Patients with TACSTD2-high breast, CRC, and pancreatic cancers demonstrated a significantly shorter OS than TACSTD2-low tumors. This was restricted to CRC with microsatellite stable tumors and patients with pancreatic cancer with KRAS-mutant tumors. Patients with breast cancer with TACSTD2-high tumors also experienced significantly worse OS following immune checkpoint inhibitors. CONCLUSIONS: TACSTD2 expression is associated with key driver alterations and a more active immune microenvironment, suggesting possible combinatorial strategies with TROP2-targeting ADCs plus immunotherapy in various solid tumors.
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BACKGROUND: Mutations in KRAS and NRAS are associated with a lack of response to cetuximab and panitumumab, two biologics used for third-line therapy of metastatic colorectal cancer (mCRC). In British Columbia, Canada, eligibility for cetuximab or panitumumab was first based on single-gene KRAS testing. OncoPanel, a multi-gene next-generation sequencing panel with both KRAS and NRAS, was introduced in 2016. Our objective was to estimate the real-world cost-effectiveness of OncoPanel versus to single-gene KRAS testing to inform eligibility for cetuximab or panitumumab in mCRC. METHODS: Using population-based administrative health data, we identified a cohort of mCRC patients who had received a KRAS or OncoPanel test, and completed prior chemotherapy in 2010-2019. We matched KRAS- and OncoPanel-tested patients (1:1) using genetic matching to balance baseline covariates. Mean and incremental 3-year costs, survival, and quality-adjusted survival were estimated using inverse-probability-of-censoring weighting and bootstrapping. We conducted scenario-based sensitivity analysis for key costs and assumptions. FINDINGS: All OncoPanel-tested cases (n=371) were matched to a KRAS-tested comparator. In the KRAS and OncoPanel groups, respectively, 55·8â¯% and 41·2â¯% of patients were potentially eligible for cetuximab or panitumumab based on mutation status. Incremental cost and effectiveness of OncoPanel were $72 (95â¯% CI: -6387, 6107), -0·004 life-years (95â¯% CI: -0·119, 0·113), and -0·011 quality-adjusted life-years (95â¯% CI: -0·094, 0·075). Reductions in systemic therapy costs were offset by increased costs in other resources. Results were moderately sensitive to time horizon and changes in testing or treatment cost. INTERPRETATION: The use of OncoPanel resulted in more precise targeting of cetuximab and panitumumab, but there was no change in incremental cost or quality-adjusted survival. Understanding the balance of costs achieved in practice can provide insight into the effect of future changes in testing policy, test cost, treatment eligibility, or drug prices in this setting.
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Precision oncology has a significant role to play in delivering optimal patient care. Biomarkers are critical enablers for precision oncology across the continuum of cancer diagnosis, in defining patient prognosis, and in predicting the response to treatments and their potential toxicities, as well as delineating the risk of hereditary cancer syndromes. Biomarkers also potentiate cancer drug development, accelerating patient access to safe and effective therapies. However, despite an accurate and timely diagnosis being critical to patient survival, advances in genomic testing are not being fully exploited in daily clinical practice, leading to missed opportunities to deliver the most effective treatments for patients. Biomarker testing availability and implementation often lag behind approvals of respective biomarker-informed therapies, limiting prompt patient access to these life-saving drugs. Multiple factors currently impede the routine adoption of biomarker testing including, but not limited to, cost, lack of test reimbursement, limited access, regulatory hurdles, lack of knowledge, insufficient cooperation on assay development, and the urgent need to harmonize and validate testing assays, all leading to inefficient diagnostic pathways. Clinical guidelines increasingly include genomic profiling, and recent evidence suggests that precision oncology can be delivered in a cost-effective way for financially-challenged health systems. Therefore, precision genomic testing for cancer biomarkers must be embedded into the clinical practice of oncology care delivery going forward. We articulate a series of recommendations and a call to action to underpin the mainstreaming of a biomarker-informed precision oncology approach to enhance patient outcomes and deliver cost effective 21st century cancer care.
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Cancer remains a significant global health challenge due to its high morbidity and mortality rates. Early detection is essential for improving patient outcomes, yet current diagnostic methods lack the sensitivity and specificity needed for identifying early-stage cancers. Here, we explore the potential of multi-omics approaches, which integrate genomic, transcriptomic, proteomic, and metabolomic data, to enhance early cancer detection. We highlight the challenges and benefits of data integration from these diverse sources and discuss successful examples of multi-omics applications in other fields. By leveraging these advanced technologies, multi-omics can significantly improve the sensitivity and specificity of early cancer diagnostics, leading to better patient outcomes and more personalized cancer care. We underscore the transformative potential of multi-omics approaches in revolutionizing early cancer detection and the need for continued research and clinical integration.
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The regulatory approvals of tumor-agnostic therapies have led to the re-evaluation of the drug development process. The conventional models of drug development are histology-based. On the other hand, the tumor-agnostic drug development of a new drug (or combination) focuses on targeting a common genomic biomarker in multiple cancers, regardless of histology. The basket-like clinical trials with multiple cohorts allow clinicians to evaluate pan-cancer efficacy and toxicity. There are currently eight tumor agnostic approvals granted by the Food and Drug Administration (FDA). This includes two immune checkpoint inhibitors, and five targeted therapy agents. Pembrolizumab is an anti-programmed cell death protein-1 (PD-1) antibody that was the first FDA-approved tumor-agnostic treatment for unresectable or metastatic microsatellite instability-high (MSI-H) or deficient mismatch repair (dMMR) solid tumors in 2017. It was later approved for tumor mutational burden-high (TMB-H) solid tumors, although the TMB cut-off used is still debated. Subsequently, in 2021, another anti-PD-1 antibody, dostarlimab, was also approved for dMMR solid tumors in the refractory setting. Patients with fusion-positive cancers are typically difficult to treat due to their rare prevalence and distribution. Gene rearrangements or fusions are present in a variety of tumors. Neurotrophic tyrosine kinase (NTRK) fusions are present in a range of pediatric and adult solid tumors in varying frequency. Larotrectinib and entrectinib were approved for neurotrophic tyrosine kinase (NTRK) fusion-positive cancers. Similarly, selpercatinib was approved for rearranged during transfection (RET) fusion-positive solid tumors. The FDA approved the first combination therapy of dabrafenib, a B-Raf proto-oncogene serine/threonine kinase (BRAF) inhibitor, plus trametinib, a mitogen-activated protein kinase (MEK) inhibitor for patients 6 months or older with unresectable or metastatic tumors (except colorectal cancer) carrying a BRAFV600E mutation. The most recent FDA tumor-agnostic approval is of fam-trastuzumab deruxtecan-nxki (T-Dxd) for HER2-positive solid tumors. It is important to identify and expeditiously develop drugs that have the potential to provide clinical benefit across tumor types.
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BACKGROUND: PIK3CA mutations are implicated in various cancers, but the implications of multiple concurrent mutations and their orientations within the gene have not been fully explored. METHODS: In this study, we analyzed multi-PIK3CA mutations across a diverse pan-cancer cohort comprising 3564 tumors. RESULTS: Multi-PIK3CA mutations were present in 10.3% of all PIK3CA-mutant tumors, predominantly occurring in breast and gynecological cancers. Notably, mutations within the helical domain (E542:E545) exclusively occurred in the trans-orientation, contrasting with mutations in the kinase ABD and C2 domains, which mainly appeared in the cis orientation. CONCLUSIONS: The distinct pattern of mutation orientations in PIK3CA suggests variable oncogenic potential, with helical domain mutations in the trans-orientation potentially being less oncogenic. These findings highlight the importance of mutation orientation in the PIK3CA gene as potential biomarkers for targeted therapy. This understanding is crucial for designing clinical trials that leverage PI3K inhibitors, aiming for more effective and precise cancer treatment.
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Classe I de Fosfatidilinositol 3-Quinases , Mutação , Neoplasias , Medicina de Precisão , Humanos , Classe I de Fosfatidilinositol 3-Quinases/genética , Neoplasias/genética , Medicina de Precisão/métodos , Biomarcadores Tumorais/genética , FemininoRESUMO
Technological advancements in cell-free DNA (cfDNA) liquid biopsy have triggered exponential growth in numerous clinical applications. While cfDNA-based liquid biopsy has made significant strides in personalizing cancer treatment, the exploration and translation of epigenetics in liquid biopsy to clinical practice is still nascent. This comprehensive review seeks to provide a broad yet in-depth narrative of the present status of epigenetics in cfDNA liquid biopsy and its associated challenges. It highlights the potential of epigenetics in cfDNA liquid biopsy technologies with the hopes of enhancing its clinical translation. The momentum of cfDNA liquid biopsy technologies in recent years has propelled epigenetics to the forefront of molecular biology. We have only begun to reveal the true potential of epigenetics in both our understanding of disease and leveraging epigenetics in the diagnostic and therapeutic domains. Recent clinical applications of epigenetics-based cfDNA liquid biopsy revolve around DNA methylation in screening and early cancer detection, leading to the development of multi-cancer early detection tests and the capability to pinpoint tissues of origin. The clinical application of epigenetics in cfDNA liquid biopsy in minimal residual disease, monitoring, and surveillance are at their initial stages. A notable advancement in fragmentation patterns analysis has created a new avenue for epigenetic biomarkers. However, the widespread application of cfDNA liquid biopsy has many challenges, including biomarker sensitivity, specificity, logistics including infrastructure and personnel, data processing, handling, results interpretation, accessibility, and cost effectiveness. Exploring and translating epigenetics in cfDNA liquid biopsy technology can transform our understanding and perception of cancer prevention and management. cfDNA liquid biopsy has great potential in precision oncology to revolutionize conventional ways of early cancer detection, monitoring residual disease, treatment response, surveillance, and drug development. Adapting the implementation of liquid biopsy workflow to the local policy worldwide and developing point-of-care testing holds great potential to overcome global cancer disparity and improve cancer outcomes.
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Background: Metastatic colon adenocarcinoma presents significant challenges in treatment, particularly when resistant to standard therapies. Precision oncology, guided by multidisciplinary tumor boards (MTBs), offers a promising way for individualized therapeutic approaches. Integration of comprehensive genomic profiling (CGP) and minimal residual disease (MRD) testing strengthens treatment decision-making, yet challenges persist in identifying and overcoming resistance mechanisms. FLT3 amplification can be one of those resistance/escape mechanisms that needs to be targeted. Case presentation: This case report presents a 58-year-old male diagnosed with metastatic colon adenocarcinoma with liver metastasis, resistant to conventional treatments. Utilizing CGP and MRD testing, our multidisciplinary MTB identified a complex mutational profile, including APC, DAXX, TP53 mutations, and CDK8 and FLT3 amplifications. With a tumor mutational burden of 10 muts/mb and TPS, CPS scores of 0, immunotherapy was considered, employing dual immune checkpoint inhibitors alongside mebendazole and Lenvatinib targeting the WNT and VEGF/angiogenesis pathways. MRD testing revealed early treatment failure. Re-evaluation identified high copied FLT3 amplification (62 copies) as a resistance mechanism, prompting modification to incorporate sorafenib and dual immunotherapy with mebendazole. Subsequent MRD assessments and radiological scans demonstrated a remarkable therapeutic response, with sustained efficacy and absence of detectable residual disease. Conclusion: This case highlights the successful application of precision oncology principles, facilitated by dynamic MTB-guided treatment strategies. Integration of MRD testing provided early detection of treatment inefficacy, allowing for timely intervention and adaptation of the treatment plan. Additionally, the case highlights the educational value of rare molecular alterations, emphasizing continual learning and refinement of treatment approaches in precision oncology.
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BACKGROUND: Heterogeneity can impact biomarker identification. Thus, we investigated the somatic copy number alterations (SCNAs) of individual tumor cells in the vitreous humor of a retinoblastoma patient using single-cell whole-genome profiling and explored the genomic concordance among vitreous and aqueous humor, vitreous seeds, and tumor. METHODS: Aqueous humor (AH), vitreous humor (VH), and tumor biopsy were obtained from an enucleated globe with retinoblastoma and vitreous seeding. Micromanipulation was used to manually isolate 39 live single tumor cells from vitreous seeds harvested from the VH. The SCNA profiles of these individual cells were generated via whole-genome sequencing and analyzed alongside profiles from the tumor mass and cell-free DNA (cfDNA) from AH and VH. RESULTS: Heatmap of VH single-cell SCNA profiles demonstrates heterogeneity among individual vitreous seeds with one clearly dominant subclone (23 of 37 cells). The SCNA profiles from the cells in this subclone demonstrate an average concordance of 98% with cfDNA profiles from acellular AH and VH and with the tumor profile. CONCLUSIONS: Our findings reveal some heterogeneity among single-cell SCNA profiles in individual VH seeds. Despite this heterogeneity, the dominant vitreous subclone exhibits extremely (>98%) high concordance with the SCNA profile from tumor and AH, suggesting AH cfDNA is representative of the dominant genomic subclone. This may facilitate tumoral biomarker identification via the AH. This preliminary work supports the potential of applying single-cell technology to VH seeds in retinoblastoma as a platform to study tumor subclones, which may provide insight into the genomic complexity of disease.
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INTRODUCTION: Antibody-drug conjugates (ADCs) represent a revolutionary approach in the systemic treatment for both solid and hematologic tumors. Constituted by an antibody, a cytotoxic payload, and a linker, ADCs aim to selectively deliver cytotoxic agents to tumors while sparing normal tissues. Various ADCs have been tested and approved for multiple solid tumors so far, but if there is one that had a major impact on clinical practice, this is Trastuzumab-deruxtecan (T-DXd). Notably, T-DXd was approved for HER2-positive and HER2-low metastatic breast cancer (MBC), HER2-positive gastric cancer (GC), HER2-mutant non-small cell lung cancer (NSCLC) and HER2 3+ solid tumors. Moreover, it received Breakthrough Therapy Designation for HER2-positive colorectal cancer (CRC). AREAS COVERED: We review preclinical and clinical data of T-DXd, focusing on early-phase ongoing trials exploring combination therapies to enhance the activity of T-DXd in HER2-expressing solid tumors. EXPERT OPINION: The clinical use of T-DXd still raises questions about selection of patients, treatment duration, prioritization over other approved ADCs, and management of resistance. Concerns regarding the toxicity of T-DXd remain, particularly with combinations involving potentially toxic drugs. Advancements in biomarker identification and combination therapies offer promising avenues to enhance efficacy and overcome resistance to T-DXd, ultimately improving outcomes for patients with cancer.
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Camptotecina , Desenvolvimento de Medicamentos , Imunoconjugados , Receptor ErbB-2 , Trastuzumab , Humanos , Imunoconjugados/farmacologia , Imunoconjugados/administração & dosagem , Imunoconjugados/efeitos adversos , Receptor ErbB-2/metabolismo , Trastuzumab/farmacologia , Trastuzumab/administração & dosagem , Animais , Camptotecina/farmacologia , Camptotecina/análogos & derivados , Camptotecina/administração & dosagem , Camptotecina/efeitos adversos , Neoplasias/tratamento farmacológico , Neoplasias/patologia , Antineoplásicos Imunológicos/farmacologia , Antineoplásicos Imunológicos/administração & dosagem , Antineoplásicos Imunológicos/efeitos adversosRESUMO
INTRODUCTION: Despite several therapeutic advancements, the proportion of patients with advanced biliary tract cancers (BTC) surviving 5 years from diagnosis remains dismal. The increasing recognition of targetable genetic alterations in BTCs has ushered in a new era in the treatment of these patients. Newer therapeutic agents targeting mutations such as isocitrate dehydrogenase (IDH), fibroblastic growth factor receptor (FGFR), human epidermal growth factor receptor (HER), and so on have established a new standard of care for treatment upon progression on frontline therapy in patients with disease harboring these mutations. AREAS COVERED: The current review aims to concisely summarize progress with various targeted therapy options for BTC. We also briefly discuss future directions in clinical and translational research for the adoption of a personalized approach for the treatment of unresectable or advanced BTC. EXPERT OPINION: Several new agents continue to emerge as feasible treatment options for patients with advanced BTC harboring targetable mutations. There is a growing need to identify mechanisms to conquer primary and acquired resistance to these agents. The identification of potential biomarkers that predict response to targeted therapy may be helpful in adopting a more tailored approach. All patients receiving treatment for advanced BTC should undergo tissue genomic profiling at diagnosis.
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Antineoplásicos , Neoplasias do Sistema Biliar , Terapia de Alvo Molecular , Mutação , Medicina de Precisão , Humanos , Neoplasias do Sistema Biliar/tratamento farmacológico , Neoplasias do Sistema Biliar/patologia , Neoplasias do Sistema Biliar/genética , Antineoplásicos/farmacologia , Antineoplásicos/administração & dosagem , Resistencia a Medicamentos Antineoplásicos , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , Taxa de Sobrevida , Progressão da Doença , AnimaisRESUMO
Genomic profiling of hundreds of cancer-associated genes is now a component of routine cancer care. DNA sequencing can identify mutations, mutational signatures, and structural alterations predictive of therapy response and assess for heritable cancer risk, but it has been less useful for identifying predictive biomarkers of sensitivity to cytotoxic chemotherapies, antibody drug conjugates, and immunotherapies. The clinical adoption of molecular profiling platforms such as RNA sequencing better suited to identifying those patients most likely to respond to immunotherapies and drug combinations will be critical to expanding the benefits of precision oncology. This review discusses the potential advantages of innovative molecular and functional profiling platforms designed to replace or complement targeted DNA sequencing and the major hurdles to their clinical adoption.
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BACKGROUND: Providing appropriate specialized treatment to the right patient at the right time is considered necessary in cancer management. Targeted therapy tailored to the genetic changes of each breast cancer patient is a desirable feature of precision oncology, which can not only reduce disease progression but also potentially increase patient survival. The use of artificial intelligence alongside precision oncology can help physicians by identifying and selecting more effective treatment factors for patients. METHOD: A systematic review was conducted using the PubMed, Embase, Scopus, and Web of Science databases in September 2023. We performed the search strategy with keywords, namely: Breast Cancer, Artificial intelligence, and precision Oncology along with their synonyms in the article titles. Descriptive, qualitative, review, and non-English studies were excluded. The quality assessment of the articles and evaluation of bias were determined based on the SJR journal and JBI indices, as well as the PRISMA2020 guideline. RESULTS: Forty-six studies were selected that focused on personalized breast cancer management using artificial intelligence models. Seventeen studies using various deep learning methods achieved a satisfactory outcome in predicting treatment response and prognosis, contributing to personalized breast cancer management. Two studies utilizing neural networks and clustering provided acceptable indicators for predicting patient survival and categorizing breast tumors. One study employed transfer learning to predict treatment response. Twenty-six studies utilizing machine-learning methods demonstrated that these techniques can improve breast cancer classification, screening, diagnosis, and prognosis. The most frequent modeling techniques used were NB, SVM, RF, XGBoost, and Reinforcement Learning. The average area under the curve (AUC) for the models was 0.91. Moreover, the average values for accuracy, sensitivity, specificity, and precision were reported to be in the range of 90-96% for the models. CONCLUSION: Artificial intelligence has proven to be effective in assisting physicians and researchers in managing breast cancer treatment by uncovering hidden patterns in complex omics and genetic data. Intelligent processing of omics data through protein and gene pattern classification and the utilization of deep neural patterns has the potential to significantly transform the field of complex disease management.