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The discovery of KRAS mutations, particularly the KRASG12C variant, has been a milestone in understanding the molecular underpinnings of non-small cell lung cancer (NSCLC). These mutations are associated with aggressive tumor behavior and resistance to conventional therapies, highlighting the urgent need for targeted interventions. In this comprehensive review, we analyze the advancements in KRAS G12C inhibitors for the treatment of non-small cell lung cancer. Literature search is made from PubMed, Medline ASCO and ESMO Annual Meetings abstracts by using the following search keywords: "sotorasib", "adagrasib", "divarasib" and "KRAS G12C inhibitors." The last search was on 5 June 2024. This review highlights the importance of pharmacokinetics, pharmacodynamics and potential adverse effects for treating individual patients and ensuring the best outcomes. Additionally, the review discusses research identifying biomarkers that can predict therapy responses and mentions the combination strategies to overcome resistance. Results of the studies and ongoing clinical trials are also briefly summarized in this review. KRASG12C inhibitors sotorasib, adagrasib and the newer divarasib, has revolutionized treating patients harboring this mutation. Ongoing studies and future clinical trials will refine our understandings with the ultimate goal of improving survival and quality of life for patients with this challenging disease.

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BACKGROUND AND OBJECTIVE: The 2024 US Food and Drug Administration approval of erdafitinib for the treatment of metastatic urothelial carcinoma (mUC) with FGFR3 alterations ushered in the era of targeted therapy for bladder cancer. In this review, we summarize the effects of FGFR pathway alterations in oncogenesis, clinical data supporting FGFR inhibitors in the management of bladder cancer, and the challenges that remain. METHODS: Original articles relevant to FGFR inhibitors in urothelial cancer between 1995 and 2024 were systematically identified in the PubMed and MEDLINE databases using the search terms "FGFR" and "bladder cancer". An international expert panel with extensive experience in FGFR inhibitor treatment was convened to synthesize a collaborative narrative review. KEY FINDINGS AND LIMITATIONS: Somatic FGFR3 alterations are found in up to 70% of low-grade non-muscle-invasive bladder cancers; these activate downstream signaling cascades and culminate in cellular proliferation. Beyond a link to lower-grade/lower-stage tumors, there is little consistency regarding whether these alterations confer prognostic risks for cancer recurrence or progression. FGFR3-altered tumors have been linked to a non-inflamed tumor microenvironment, but paradoxically do not seem to impact the response to systemic immunotherapy. Several pan-FGFR inhibitors have been investigated in mUC. With the introduction of novel intravesical drug delivery systems, FGFR inhibitors are poised to transform the therapeutic landscape for early-stage UC. CONCLUSIONS AND CLINICAL IMPLICATIONS: With deepening understanding of the biology of bladder cancer, novel diagnostics, and improved drug delivery methods, we posit that FGFR inhibition will lead the way in advancing precision treatment of bladder cancer.

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Accurate estimation of tumor mutational burden (TMB) as a predictor of responsiveness to immune checkpoint inhibitors in gene panel assays requires an adequate panel size. The current calculations of TMB only consider coding regions, while most of gene panel assays interrogate non-coding regions. Leveraging the non-coding regions is a potential solution to address this panel size limitation. However, the impact of including non-coding regions on the accuracy of TMB estimates remains unclear. This study investigated the validity of leveraging non-coding regions to supplement panel size using the OncoGuide NCC Oncopanel System (NOP). The aim of this study was to evaluate test performance against orthogonal assays and the association with responsiveness to immune checkpoint inhibitors was not included in the evaluation. We compared TMB status and values between TMB calculated only from coding regions (NOP-coding) and from both coding and non-coding regions (NOP-overall) using whole exome sequencing (WES) and FoundationOne®CDx (F1CDx) assay. Our findings revealed that NOP-overall significantly improved the overall percent agreement (OPA) with TMB status compared with NOP-coding for both WES (OPA: 96.7% vs. 73.3%, n = 30) and F1CDx (OPA: 90.0% vs. 73.3%). Additionally, the mean difference in TMB values compared with WES was lower for NOP-overall (3.55 [95% CI: 0.98-6.13]) than for NOP-coding (6.22 [95% CI: 3.73-8.70]). These results exemplify the utility of incorporating non-coding regions to maintain accurate TMB estimates in small-sized panels.

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INTRODUCTION: This study assesses the effectiveness of durvalumab with platinum and gemcitabine for biliary tract cancers (BTC). It aims to confirm the TOPAZ-1 trial results in a real-world context and explore the link between BTC molecular profiles and patient outcomes. METHODS: A retrospective analysis was conducted on 102 BTC patients treated with durvalumab, platinum, and gemcitabine at five cancer centers in Austria and one in Germany from 2022 to 2024. Molecular profiling used targeted DNA and RNA assays. Clinical endpoints, including progression-free survival (PFS) and overall survival (OS), were assessed using log-rank tests and Cox regression, with correlations to second-line molecular-targeted therapies. RESULTS: Among 102 patients, 60.8% had intrahepatic cholangiocarcinoma. The treatment achieved a disease control rate of 71.57% and an overall response rate of 35.11%. Median PFS was 6.51 months, and OS was 13.61 months. Patients under 65 had significantly better OS. Alterations in chromatin remodeling or homologous recombination repair genes were not predictive of survival benefit (HR: 0.45; p = 0.851 and HR: 1.63; p = 0.26, respectively). Patients with molecular-informed second-line therapy showed a trend toward survival benefit (HR: 0.23; p = 0.052). CONCLUSION: This study confirms the phase 3 trial results of durvalumab with platinum and gemcitabine, providing a substantial real-world dataset with detailed molecular characterization. No specific patient subgroup showed a markedly better response to durvalumab based on conventional NGS panels. Further research is needed to explore the link between immunotherapy responses and molecular subgroups.

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Lung cancer (LC) is a significant global health issue, particularly among smokers, and is characterized by high rates of incidence and mortality. This comprehensive review offers detailed insights into the potential of artificial intelligence (AI) to revolutionize early detection and personalized treatment strategies for LC. By critically evaluating the limitations of conventional methodologies, we emphasize the innovative potential of AI-driven risk prediction models and imaging analyses to enhance diagnostic precision and improve patient outcomes. Our in-depth analysis of the current state of AI integration in LC care highlights the achievements and challenges encountered in real-world applications, thereby shedding light on practical implementation. Furthermore, we examined the profound implications of AI on treatment response, survival rates, and patient satisfaction, addressing ethical considerations to ensure responsible deployment. In the future, we will outline emerging technologies, anticipate potential barriers to their adoption, and identify areas for further research, emphasizing the importance of collaborative efforts to fully harness the transformative potential of AI in reshaping LC therapy. Ultimately, this review underscores the transformative impact of AI on LC care and advocates for a collective commitment to innovation, collaboration, and ethical stewardship in healthcare.

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Ovarian cancer, predominantly epithelial ovarian cancer (EOC), is a global health concern due to its high mortality rate. Despite the progress made during the last two decades in the surgery and chemotherapy of ovarian cancer, more than 70% of advanced patients are with recurrent cancer and disease. Bevacizumab is a humanized monoclonal antibody, which blocks VEGF signaling in cancer, inhibits angiogenesis and causes tumor shrinkage, and has been recently approved by the FDA as a monotherapy for advanced ovarian cancer in combination with chemotherapy. Unfortunately, Bevacizumab may also induce harmful adverse effects, such as hypertension, bleeding, arterial thromboembolism, poor wound healing and gastrointestinal perforation. Given the expensive cost and unwanted toxicities, there is an urgent need for predictive methods to identify who could benefit from bevacizumab. Of the 18 (approved) requests from 5 countries, 6 teams using 284 whole section WSIs for training to develop fully automated systems submitted their predictions on a test set of 180 tissue core images, with the corresponding ground truth labels kept private. This paper summarizes the 5 qualified methods successfully submitted to the international challenge of automated prediction of treatment effectiveness in ovarian cancer using the histopathologic images (ATEC23) held at the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) in 2023 and evaluates the methods in comparison with 5 state of the art deep learning approaches. This study further assesses the effectiveness of the presented prediction models as indicators for patient selection utilizing both Cox proportional hazards analysis and Kaplan-Meier survival analysis. A robust and cost-effective deep learning pipeline for digital histopathology tasks has become a necessity within the context of the medical community. This challenge highlights the limitations of current MIL methods, particularly within the context of prognosis-based classification tasks, and the importance of DCNNs like inception that has nonlinear convolutional modules at various resolutions to facilitate processing the data in multiple resolutions, which is a key feature required for pathology related prediction tasks. This further suggests the use of feature reuse at various scales to improve models for future research directions. In particular, this paper releases the labels of the testing set and provides applications for future research directions in precision oncology to predict ovarian cancer treatment effectiveness and facilitate patient selection via histopathological images.

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Background: Transcriptomics can reveal much about cellular activity, and cancer transcriptomics have been useful in investigating tumor cell behaviors. Patterns in transcriptome-wide gene expression can be used to investigate biological mechanisms and pathways that can explain the variability in patient response to cancer therapies. Methods: We identified gene expression patterns related to patient drug response by clustering tumor gene expression data and selecting from the resulting gene clusters those where expression of cluster genes was related to patient survival on specific drugs. We then investigated these gene clusters for biological meaning using several approaches, including identifying common genomic locations and transcription factors whose targets were enriched in these clusters and performing survival analyses to support these candidate transcription factor-drug relationships. Results: We identified gene clusters related to drug-specific survival, and through these, we were able to associate observed variations in patient drug response to specific known biological phenomena. Specifically, our analysis implicated 2 stem cell-related transcription factors, HOXB4 and SALL4, in poor response to temozolomide in brain cancers. In addition, expression of SNRNP70 and its targets were implicated in cetuximab response by 3 different analyses, although the mechanism remains unclear. We also found evidence that 2 cancer-related chromosomal structural changes may impact drug efficacy. Conclusion: In this study, we present the gene clusters identified and the results of our systematic analysis linking drug efficacy to specific transcription factors, which are rich sources of potential mechanistic relationships impacting patient outcomes. We also highlight the most promising of these results, which were supported by multiple analyses and by previous research. We report these findings as promising avenues for independent validation and further research into cancer treatments and patient response.

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Rationale: PSMA-targeting radioligand therapy (PSMA-RLT) has shown promise in metastatic castration-resistant prostate cancer (mCRPC), particularly in PSMA-avid tumours. However, predicting response remains challenging. Preclinical data suggests aberrant p53-signalling as a predictor of poor response. Methods: The patient population of this pre-planned retrospective cohort study consists of 96 patients with mCRPC who underwent treatment with PSMA-RLT and were molecularly profiled by whole-genome sequencing and or targeted next-generation sequencing. Response to PSMA-RLT was assessed per molecular subtype, including TP53-mutational status. Results: Patients with TP53 loss-of-function alterations had a shorter median progression-free survival (3.7 versus 6.2 months, P<0.001), a lower median PSA change (-55% vs. -75%, P=0.012) and shorter overall survival from initiation of PMSA-RLT (7.6 vs. 13.9 months, P=0.003) compared to TP53-wildtype patients. Pathogenic alterations in AR, MYC, BRCA1, or BRCA2 as well as in genes linked to the PI3K or MAPK pathways or genes involved in homologous recombination repair, were not associated with response. Only lactate dehydrogenase was, alongside TP53-status, significantly associated with response. Transcriptome analysis of 21 patients, identified six p53 signalling genes whose low expression was associated to a shorter progression-free survival (P<0.05). Conclusion: TP53 loss-of-function may serve as a prognostic factor for PSMA-RLT outcomes in patients with mCRPC.

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The use of companion diagnostics has become a standard in precision oncology in the context of ongoing therapeutic innovation. However, certain limitations make their application imperfect in current practice. This position paper underscores the need to broaden the notion of companion testing, considering the potential of emerging technologies, including computational biology, to overcome these limitations. This wave of progress should impact not only our representation of the analytical tool itself but also the nature of the tumoral sample under analysis (liquid biopsies). The complex inter-relationship between companion test guided-personalized therapy, and health agency policies for new drug agreements will also be discussed.

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PURPOSE: To assess safety and feasibility of percutaneous MR-guided placement of an implantable microdevice (IMD) to evaluate in situ intratumor response to multiple pharmacologic agents in men with intermediate- and high-risk localized prostate cancer. MATERIALS AND METHODS: Biocompatible IMDs measuring 750um in diameter and 5 mm in length were prepared with 20 reservoirs containing candidate drug and drug combinations including second-generation androgen inhibitors, PARP inhibitors, PD-1 inhibitors and conventional chemotherapy. Men with intermediate- or high-risk localized prostate cancer and MRI-visible lesions were enrolled. Up to 4 IMDs were placed via transperineal approach into MRI-visible tumors two days before planned radical prostatectomy. After radical prostatectomy, the IMDs and a small segment of surrounding tumor tissue were removed and sectioned, stained, and analyzed for tissue drug response by a variety of pharmacodynamic markers. RESULTS: 14 patients were enrolled, 7 (50%) with intermediate-risk and 7 (50%) with high-risk localized prostate cancer. A total of 53 IMDs were implanted (mean 3.8 per patient) and 49 (92%) IMDs were successfully retrieved. All men underwent uncomplicated robotic radical prostatectomy and bilateral pelvic lymph node dissection 2 days after IMD placement. There were no severe adverse events. Pathological examination of the tissues adjacent to the IMDs demonstrated differential drug response within patients and between patients. Limitations include small sample size. CONCLUSIONS: A multi-drug IMD can be safely placed percutaneously into MRI-visible lesions before radical prostatectomy, enabling assessment of tumor-specific local response to multiple agents simultaneously within the tumor's normal stromal environment to guide targeted systemic therapy.

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Objectives: Human epidermal growth factor receptor 2 (HER2)-targeted therapies have demonstrated potential benefits for metastatic colorectal cancer (mCRC) patients with HER2 amplification, but are not satisfactory in cases of HER2 mutant CRCs. Methods: Consequently, further elucidation of amplifications and somatic mutations in erythroblastic oncogene B-2 (ERBB2) is imperative. Comprehensive genomic profiling was conducted on 2454 Chinese CRC cases to evaluate genomic alterations in 733 cancer-related genes, tumor mutational burden, microsatellite instability, and programmed death ligand 1 (PD-L1) expression. Results: Among 2454 CRC patients, 85 cases (3.46%) exhibited ERBB2 amplification, and 55 cases (2.24%) carried ERBB2 mutation. p.R678Q (28%), p.V8421 (24%), and p.S310F/Y (12%) were the most prevalent of the 16 detected mutation sites. In comparison to the ERBB2 altered (alt) group, KRAS/BRAF mutations were more prevalent in ERBB2 wild-type (wt) samples (ERBB2wt vs. ERBB2alt, KRAS: 50.9% vs. 25.6%, p < 0.05; BRAF: 8.5% vs. 2.3%, p < 0.05). 32.7% (18/55) of CRCs with ERBB2 mutation exhibited microsatellite instability high (MSI-H), while no cases with HER2 amplification displayed MSI-H. Mutant genes varied between ERBB2 copy number variation (CNV) and ERBB2 single nucleotide variant (SNV); TP53 alterations tended to co-occur with ERBB2 amplification (92.3%) as opposed to ERBB2 mutation (58.3%). KRAS and PIK3CA alterations were more prevalent in ERBB2 SNV cases (KRAS/PIK3CA: 45.8%/31.2%) compared to ERBB2 amplification cases (KRAS/PIK3CA: 14.1%/7.7%). Conclusion: Our study delineates the landscape of HER2 alterations in a large-scale cohort of CRC patients from China. These findings enhance our understanding of the molecular features of Chinese CRC patients and offer valuable implications for further investigation.

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Background: Head and neck squamous cell carcinoma (HNSC) is the most prevalent cancer in the head and neck region, originating from the mucosal epithelium of the oral cavity, pharynx, and larynx. The solute carrier (SLC) transporter superfamily, consisting of over 400 proteins across 65 families, plays a crucial role in cellular functions and presents promising targets in precision oncology. This study aims to analyze the expression of SLC transporters in HNSC and their potential as biomarkers and therapeutic targets. Methods: We leveraged mRNA and protein expression data from The Cancer Genome Atlas (TCGA) and The Human Protein Atlas (HPA) to examine SLC transporter expression in HNSC. Gene Set Enrichment Analysis (GSEA) was conducted to assess the involvement of SLC transporters in various oncogenic pathways. Results: Significant upregulation of SLC transporters was observed in tumor tissues compared to normal tissues, with notable increases in SLC16A3, SLC53A1, SLC25A32, and SLC2A3. This upregulation correlated with poorer overall survival (OS) and disease-specific survival (DSS). GSEA revealed that these transporters are significantly involved in critical oncogenic pathways, including epithelial-mesenchymal transition (EMT), angiogenesis, and hypoxia, which are vital for cancer progression and metastasis. Conclusions: The study identifies SLC transporters as potential biomarkers and therapeutic targets in HNSC. Targeting these transporters with small molecule inhibitors could disrupt essential supply routes for cancer cells, enhancing treatment efficacy and improving patient outcomes. This study paves the way for developing SLC-based target therapies in precision oncology, with the goal of improving survival rates for patients with HNSC.

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BACKGROUND: Next-generation sequencing (NGS) has become widely available but molecular profiling-guided therapy (MGT) had not been well established in the real world due to lack of available therapies and expertise to match treatment. Our study was designed to test the feasibility of a nationwide platform of NGS-guided MGT recommended by a central molecular tumor board (cMTB) for metastatic solid tumors. PATIENTS AND METHODS: Patients with advanced or metastatic solid tumors with available NGS results and without standard treatment were enrolled. The cMTB interpreted the patients' NGS reports and recommended the following: (i) investigational medicinal products (IMPs) approved in other indications; (ii) alternative treatments; (iii) clinical trials. The primary variables were the proportion of patients with actionable genomic alterations and those receiving MGT as per cMTB recommendations. Others included treatment duration (TD), overall response rate (ORR), disease control rate (DCR), and safety. RESULTS: From February 2021 to February 2022, 193 cases [99 (51.3%) men; median age 58 years (range 24-88 years); median line of previous treatment 3 (range 0-9)] from 29 sites were enrolled for 60 cMTB sessions. The median time from case submission to cMTB discussion was 7 days (range 2-20 days), and to IMP treatment initiation was 28 days (range 14-90 days). Actionable genetic alterations were found in 145 patients (75.1%). A total of 89 (46.1%) patients received actual dosing of IMPs, and 10 (5.2%) were enrolled in cMTB-recommended clinical trials, achieving an MGT rate of 51.3%. ORR and DCR of IMPs were 10.1% and 72.5%, respectively. The median TD was 3.5 months [95% confidence interval (CI) 2.8-5.5 months], and the 4-month TD rate was 44.9%. The median overall survival of patients who received IMPs was 6.9 months (95% CI 5.2-10.0 months). CONCLUSION: KOSMOS confirmed the feasibility of MGT recommended by the cMTB, achieving a high MGT match rate and promising effectiveness in heavily pretreated advanced cancer patients.

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INTRODUCTION: Whole Exome Sequencing (WES) has emerged as an efficient tool in clinical cancer diagnostics to broaden the scope from panel-based diagnostics to screening of all genes and enabling robust determination of complex biomarkers in a single analysis. METHODS: To assess concordance, six formalin-fixed paraffin-embedded (FFPE) tissue specimens and four commercial reference standards were analyzed by WES as matched tumor-normal DNA at 21 NGS centers in Germany, each employing local wet-lab and bioinformatics. Somatic and germline variants, copy-number alterations (CNAs), and complex biomarkers were investigated. Somatic variant calling was performed in 494 diagnostically relevant cancer genes. The raw data were collected and re-analyzed with a central bioinformatic pipeline to separate wet- and dry-lab variability. RESULTS: The mean positive percentage agreement (PPA) of somatic variant calling was 76 % while the positive predictive value (PPV) was 89 % in relation to a consensus list of variants found by at least five centers. Variant filtering was identified as the main cause for divergent variant calls. Adjusting filter criteria and re-analysis increased the PPA to 88 % for all and 97 % for the clinically relevant variants. CNA calls were concordant for 82 % of genomic regions. Homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI) status were concordant for 94 %, 93 %, and 93 % of calls, respectively. Variability of CNAs and complex biomarkers did not decrease considerably after harmonization of the bioinformatic processing and was hence attributed mainly to wet-lab differences. CONCLUSION: Continuous optimization of bioinformatic workflows and participating in round robin tests are recommended.

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The search for dependable molecular biomarkers to enhance routine clinical practice is a compelling challenge across all oncology fields. Urothelial bladder carcinoma, known for its significant heterogeneity, presents difficulties in predicting responses to systemic therapies and outcomes post-radical cystectomy. Recent advancements in molecular cancer biology offer promising avenues to understand the disease's biology and identify emerging predictive biomarkers. Stratifying patients based on their recurrence risk post-curative treatment or predicting the efficacy of conventional and targeted therapies could catalyze personalized treatment selection and disease surveillance. Despite progress, reliable molecular biomarkers to forecast responses to systemic agents, in neoadjuvant, adjuvant, or palliative treatment settings, are still lacking, underscoring an urgent unmet need. This review aims to delve into the utilization of current and emerging molecular signatures across various stages of urothelial bladder carcinoma to predict responses to systemic therapy.

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A multitude of exogenous and endogenous processes have the potential to result in DNA damage. While the repair mechanisms are typically capable of correcting this damage, errors in the repair process can result in mutations. The findings of research conducted in 2012 indicate that mutations do not occur randomly but rather follow specific patterns that can be attributed to known or inferred mutational processes. The process of mutational signature analysis allows for the inference of the predominant mutational process for a given cancer sample, with significant potential for clinical applications. A deeper comprehension of these mutational signatures in CRC could facilitate enhanced prevention strategies, facilitate the comprehension of genotoxic drug activity, predict responses to personalized treatments, and, in the future, inform the development of targeted therapies in the context of precision oncology. The efforts of numerous researchers have led to the identification of several mutational signatures, which can be categorized into different mutational signature references. In CRC, distinct mutational signatures are identified as correlating with mismatch repair deficiency, polymerase mutations, and chemotherapy treatment. In this context, a mutational signature analysis offers considerable potential for enhancing minimal residual disease (MRD) tests in stage II (high-risk) and stage III CRC post-surgery, stratifying CRC based on the impacts of genetic and epigenetic alterations for precision oncology, identifying potential therapeutic vulnerabilities, and evaluating drug efficacy and guiding therapy, as illustrated in a proof-of-concept clinical trial.

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Nephroblastoma or Wilms' tumor (WT) is the most common pediatric renal malignancy but rare in adults. Treatment protocols for adults are typically extrapolated from pediatric guidelines, but there are no standard guidelines for adults due to the rarity of the disease. However, next-generation sequencing has led to new therapeutic options for adult WT patients. We present the first case to our knowledge of a recurrent adult WT treated with dual BRAF/MEK-targeted therapy, which showed initial robust clinical response and was well tolerated.

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Outcomes from pancreatic ductal adenocarcinoma (PDAC) remain poor and better methods of prognostication and therapeutic approaches are needed. Recent advances in cancer genomics have led to the development of molecular subtypes of PDAC associated with clinical outcomes. Current evidence also suggests that the subtypes have differential response to first-line chemotherapy regimens. PDAC is also characterized by different stroma and immune environments. Further work is needed to confirm the utility of these subtypes to predicting response to different systemic therapies.

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In the era of precision oncology, the management of triple-negative breast cancer (TNBC) is rapidly changing and becoming more complicated with a variety of chemotherapy, immunotherapy, and targeted treatment options. Currently, TNBC treatment is based on prognostic and predictive factors including immunohistochemical biomarkers [e.g. programmed death-ligand 1 (PD-L1)] and germline BRCA mutations. Given the current limitation of existing biomarkers, liquid biopsies may serve as clinically useful tools to determine treatment efficacy and response in both the (neo)adjuvant and metastatic settings, for detecting early relapse, and for monitoring clonal evolution during treatment. In this review, we comprehensively summarize current and future liquid biopsy applications. Specifically, we highlight the role of circulating tumor cell characterization, circulating tumor DNA, and other preclinical liquid biopsy technologies including circulating exosomes, RNA liquid biopsy, and circulating immune-based biomarkers. In the near future, these biomarkers may serve to identify early disease relapse, therapeutic targets, and disease clonality for patients with TNBC in the clinical setting.