Personalized Nanomedicine: Integrating Molecular Stratification with Engineered Delivery Systems

Background: Improved risk stratification for non-small cell lung cancer (NSCLC) represents a critical unmet need. A Clinical Laboratory Improvement Amendments (CLIA)-certified, 14-gene, quantitative PCR (qPCR)-based expression assay was found to better stratify mortality risk. The association of molecular risk stratification with other clinicopathological, radiomic, and genetic risk factors have not been fully identified, especially in Chinese NSCLC patients (pts). Methods: We newly recruited 102 early-stage non-squamous NSCLC pts who had undergone complete surgical resection. RNA was extracted from tumor tissue specimens and prospective molecular risk stratification by the 14-gene prognostic assay was performed. Gene mutation status and tumor mutational burden (TMB) were evaluated. Histological sections and clinical records were reviewed for canonical prognostic indicators that have been reported to be associated with lung cancer risk. Results: Of the 102 pts, the mean age was 55 years, 66 (64.7%) were female, and 18 (17.7%) had a smoking history. The majority of pts (84, 82.4%) were stage I, with 1 atypical adenomatous hyperplasia (AAH), 6 adenocarcinomas in situ (AIS), 1 stage II, and 2 stage III. 64 pts were deemed low-risk by molecular testing, 24 were intermediate-risk, and 14 were high-risk. The pts of AAH and AIS were all in the low-risk group. The maximum tumor diameter (MTD) in the high-risk group was the highest. There were no significant differences in age, sex, smoking status, pathologic stage, NCCN risk criteria, micropapillary or solid (MP/S) pattern, or the number of lesions between the three groups. The most common driver mutations were EGFR (65%), TP53 (28%), and RBM10 (13%). The molecular risk stratification had a significant association with TP53 (p = 0.013), TP53 loss of function (LOF, p = 0.01), KRAS (p = 0.011), and APC mutation (p = 0.05), but not with EGFR mutation and co-mutational status. TMB in the low-risk pts was significantly lower than in other pts (p = 0.007). The low-risk pts had lower SUVmax (p = 0.076), significantly lower mean CT value (p = 0.023), and mean enhanced CT value (p = 0.005) compared with others. In the NCCN low-risk pts, 25 were molecular low-risk, 12 were intermediate-risk, and 9 were high-risk. The risk stratification showed a significant association with SUVmax, TP53 mutation, and TMB in the NCCN low-risk pts. Pearson correlation showed the molecular risk score was significantly associated with MTD, TMB, SUVmax, mean CT value, mean enhanced CT value, and max CT value. SUVmax showed the strongest correlation with the risk score. Conclusion: The molecular risk stratification by the 14-gene assay was associated with canonical prognostic indicators, like TP53 LOF, TP53, KRAS, APC mutation, TMB, mean CT value, and mean enhanced CT value. Our study provides more evidence of the clinical utility of the qPCR-based prognostic assay. Citation Format: Naixin Liang, Jianchao Xue, Ming Zhao, Bowen Li, Yadong Wang, Zhicheng Huang, Yankai Xia, Ruirui Li, Zhongxing Bing, Zhibo Zheng, Jianpeng Zhang, Bin Wang, Zhe Feng, Xinyu Liu, Haochen Li, Xiaoqing Yu, Yang Song. Comparison of risk factors to molecular risk stratification in Chinese early-stage non-squamous non-small cell lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3312.

Sequential transcriptome analysis of human liver cancer indicates late stage acquisition of malignant traits

Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancer

Brain tumors are the most common category of childhood solid tumors. In the 1970s and 1980s, treatment protocols for benign tumors focused almost exclusively on surgery, with radiation treatment as a salvage modality, whereas the management of malignant tumors employed a combination of surgery, radiation therapy, and chemotherapy, with therapeutic approaches such as "8-in-1" chemotherapy often applied across histological tumor subsets that are now recognized to be prognostically distinct. During the ensuing years, treatment has become increasingly refined, based on clinical and, more recently, molecular factors, which have supported risk-adapted treatment stratification. The goal of this report is to provide an overview of recent progress in the field. A review of the literature was undertaken to examine recent advances in the management of the most common childhood brain tumor subsets, and in particular to identify instances in which molecular categorization and treatment stratification offer evidence or promise for improving outcome. For both medulloblastomas and infant tumors, refinements in clinical and molecular stratification have already facilitated efforts to achieve risk-adapted treatment planning. Current treatment strategies for children with these tumors focus on improving outcome for tumor subsets that have historically been relatively resistant to therapy and reducing treatment-related sequelae for children with therapy-responsive tumors. Recent advances in molecular categorization offer the promise of further refinements in future studies. For children with ependymomas and low-grade gliomas, clinical risk stratification has facilitated tailored approaches to therapy, with improvement of disease control and concomitant reduction in treatment sequelae, and recent discoveries have identified promising therapeutic targets for molecularly based therapy. In contrast, the prognosis remains poor for children with diffuse intrinsic pontine gliomas and other high-grade gliomas, despite recent identification of biological correlates of tumor prognosis and elucidation of molecular substrates of tumor development. Advances in the clinical and molecular stratification for many types of childhood brain tumors have provided a foundation for risk-adapted treatment planning and improvements in outcome. In some instances, molecular characterization approaches have also yielded insights into new therapeutic targets. For other tumor types, outcome remains discouraging, although new information regarding the biological features critical to tumorigenesis are being translated into novel therapeutic approaches that hold promise for future improvements.

Bicuspid aortic valve (BAV) is the most common congenital heart defect in human beings, with an estimated prevalence in the general population of between 0.5 and 2%. Moreover, BAV is the most common cause of aortic stenosis in the pediatric population. Patients with BAV may have no symptoms for life, and some of them may progress to aortic stenosis. Genetic factors increase the susceptibility and development of BAV. However, the pathogenesis and BAV are still unclear, and more genetic variants are still needed for elucidating the molecular mechanism and stratification of patients. The present study carried out screening of variants implicated in disease in BAV patients. The whole-exome sequencing (WES) was performed in 20 BAV patients and identified 40 different heterozygous missense mutations in 36 genes (MIB2, FAAH, S100A1, RGS16, MAP3K19, NEB, TTN, TNS1, CAND2, CCK, KALRN, ATP10D, SLIT3, ROS1, FABP7, NUP205, IL11RA, NPR2, COL5A1, CUBN, JMJD1C, ANXA7, TRIM8, LGR4, TPCN2, APOA5, GPR84, LRP1, NCOR2, AKAP11, ESRRB, NGB, AKAP13, WWOX, KCNJ12, ARHGEF1). The mutations in these genes were identified as recurrent variants implicated in disease by in silico prediction tool analysis. Nine genes (MIB2, S100A1, TTN, CCK, NUP205, LGR4, NCOR2, ESRRB, and WWOX) among the 36 genes were identified as variants implicated in disease via unanimous agreement of in silico prediction tool analysis and sequenced in an independent cohort of 137 BAV patients to validate the results of WES. BAV patients carrying these variants demonstrated reduced left ventricular ejection fractions (LVEF) (63.8 ± 7.5% vs. 58.4 ± 5.2%, P < 0.001) and larger calcification volume [(1129.3 ± 154) mm3 vs. (1261.8 ± 123) mm3, P < 0.001]. The variants in TTN, NUP205 and NCOR2 genes are significantly associated with reduced LVEF, and the variants in S100A1, LGR4, ESRRB, and WWOX genes are significantly associated with larger calcification volume. We identified a panel of recurrent variants implicated in disease in genes related to the pathogenesis of BAV. Our data speculate that these variants are promising markers for risk stratification of BAV patients with increased susceptibility to aortic stenosis.

Over the past few decades, cancer nanomedicine has been under intensive development for applications in drug delivery, cancer therapy, and molecular imaging. However, there exist a series of complex biological barriers in the path of a nanomedicine from the site of administration to the site of action. These barriers considerably prevent a nanomedicine from reaching its targets in a sufficient concentration and thus severely limit its therapeutic benefits. According to the delivery process, these biological delivery barriers can be briefly summarized in the following order: blood circulation, tumor accumulation, tumor penetration, cellular internalization, and intracellular drug release. The therapeutic effect of a nanomedicine is strongly determined by its ability to overcome these barriers. However, advances in cancer biology have revealed that each barrier has its own distinct microenvironment, which imposes different requirements on the optimal design of nanocarriers, thus further complicating the delivery process. For example, the pH of blood is neutral, while the tumor extracellular environment features an acidic pH (pHe ≈ 6.5-7.0) and the endosome and lysosome are more acidic (pH 5.5-4.5). The nanoparticles (NPs) should be able to change their properties to adapt to each individual environment for robust and effective delivery. This demand promotes the design and development of smart delivery carriers that can respond to endogenous and exogenous stimuli. It is well-documented that tumors develop acidic extracellular microenvironments with pH ≈ 6.5-7.0 due to their abnormal metabolism in comparison with normal tissues. This provides a unique tool for designing smart NP drug delivery systems. Our studies have revealed that the NPs' physiochemical properties, such as particle size and surface charge, have profound effects on their systemic transport in the body. In different delivery stages, the NPs should possess different sizes or surface charges for optimal performance. We developed a class of stimuli-responsive NPs by incorporating tumor-acidity-cleavable maleic acid amide (TACMAA) as a design feature. TACMAA is produced by the facile reaction of an amino group with 2,3-dimethylmaleic anhydride (DMMA) and its derivatives and can be cleaved under tumor acidity. By virtue of such characteristics, NPs containing TACMAA enable size or surface charge switching at tumor sites so that they can overcome those delivery barriers for improved drug delivery and cancer therapy. In this Account, we systemically review the development and evolution of TACMAA-based delivery systems and elaborate how TACMAA helps the innovation and design of intelligent nanocarriers for overcoming the delivery barriers. In particular, our Account focuses on five parts: TACMAA chemistry, tumor-acidity-triggered charge reversal, tumor-acidity-triggered shell detachment, tumor-acidity-triggered size transition, and tumor-acidity-triggered ligand reactivation. We provide detailed information on how tumor-acidity-triggered property changes correlate with the ability of NPs to overcome delivery barriers.

Urothelial cell carcinoma (UCC) of the bladder and upper urinary tract is a heterogeneous disease with distinct biologic features resulting in different clinical behaviors. Bladder cancer (BC) is classified into non-muscle invasive BC (NMIBC) and muscle invasive BC (MIBC). NMIBC is associated with high recurrence rates and risk of progression to invasive disease, whereas MIBC is complicated by systemic recurrence after radical cystectomy because of the limited efficacy of available therapies. UCC of the upper urinary tract (UUT-UCC) is a rare but aggressive urologic cancer characterized by multifocality, local recurrence, and metastasis. Conventional histopathologic evaluation of UCC, including tumor stage and grade, cannot accurately predict the behavior of BC and UUT-UCC. Recent clinical and preclinical studies aimed at understanding the molecular landscape of UCC have provided insight into molecular subtyping, inter- or intratumoral heterogeneity, and potential therapeutic targets. Combined analysis of molecular markers and standard pathological features may improve risk stratification and help monitor tumor progression and treatment response, ultimately improving patient outcomes. This review discusses prognostic and therapeutic biomarkers for BC and UUT-UCC, and describes recent advances in molecular stratification that may guide prognosis, patient stratification, and treatment selection.

AI-driven innovations in smart multifunctional nanocarriers for drug and gene delivery: A mini-review.

Molecular and Clinical Analysis of Large B-Cell Lymphomas with MYC gene Involvement: Impact of the Co-Occurrence of TP53 Deletion

Supplementary Figures S1-S4 from Molecular Risk Stratification of Medulloblastoma Patients Based on Immunohistochemical Analysis of MYC, LDHB, and CCNB1 Expression

Supplementary Figures S1-S4 from Molecular Risk Stratification of Medulloblastoma Patients Based on Immunohistochemical Analysis of MYC, LDHB, and CCNB1 Expression

&lt;div&gt;Abstract&lt;p&gt;&lt;b&gt;Purpose:&lt;/b&gt; Medulloblastoma is the most common malignant embryonal brain tumor in children. The current clinical risk stratification to select treatment modalities is not optimal because it does not identify the standard-risk patients with resistant disease or the unknown number of high-risk patients who might be overtreated with current protocols. The aim of this study is to improve the risk stratification of medulloblastoma patients by using the expression of multiple prognostic markers in combination with current clinical parameters.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Experimental Design:&lt;/b&gt; Candidate prognostic markers were selected from literature or from medulloblastoma expression data. Selected genes were immunohistochemically analyzed for their prognostic value using medulloblastoma tissue arrays containing 124 well-characterized patient samples.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Results:&lt;/b&gt; Protein expression analyses showed that the combined expression of three genes was able to predict survival in medulloblastoma patients. Low MYC expression identified medulloblastoma patients with a very good outcome. In contrast, concomitant expression of LDHB and CCNB1 characterized patients with a very poor outcome. Multivariate analyses showed that both expression of MYC and the LDHB/CCNB1 gene signature were strong prognostic markers independent of the clinical parameters metastasis and residual disease. Combined analysis of clinical and molecular markers enabled greater resolution of disease risk than clinical factors alone.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; A molecular risk stratification model for medulloblastoma patients is proposed based on the signature of MYC, LDHB, and CCNB1 expression. Combined with clinical variables, the model may provide a more accurate basis for targeting therapy in children with this disease.&lt;/p&gt;&lt;/div&gt;

&lt;div&gt;Abstract&lt;p&gt;&lt;b&gt;Purpose:&lt;/b&gt; Medulloblastoma is the most common malignant embryonal brain tumor in children. The current clinical risk stratification to select treatment modalities is not optimal because it does not identify the standard-risk patients with resistant disease or the unknown number of high-risk patients who might be overtreated with current protocols. The aim of this study is to improve the risk stratification of medulloblastoma patients by using the expression of multiple prognostic markers in combination with current clinical parameters.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Experimental Design:&lt;/b&gt; Candidate prognostic markers were selected from literature or from medulloblastoma expression data. Selected genes were immunohistochemically analyzed for their prognostic value using medulloblastoma tissue arrays containing 124 well-characterized patient samples.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Results:&lt;/b&gt; Protein expression analyses showed that the combined expression of three genes was able to predict survival in medulloblastoma patients. Low MYC expression identified medulloblastoma patients with a very good outcome. In contrast, concomitant expression of LDHB and CCNB1 characterized patients with a very poor outcome. Multivariate analyses showed that both expression of MYC and the LDHB/CCNB1 gene signature were strong prognostic markers independent of the clinical parameters metastasis and residual disease. Combined analysis of clinical and molecular markers enabled greater resolution of disease risk than clinical factors alone.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; A molecular risk stratification model for medulloblastoma patients is proposed based on the signature of MYC, LDHB, and CCNB1 expression. Combined with clinical variables, the model may provide a more accurate basis for targeting therapy in children with this disease.&lt;/p&gt;&lt;/div&gt;

Given the unique capabilities of natural cell membranes, such as prolonged blood circulation and homotypic targeting, extensive research has been devoted to developing cell membrane-inspired nanocarriers for cancer therapy, while most focused on overcoming one or a few biological barriers. In fact, the journey of nanosystems from systemic circulation to tumor cells involves intricate processes, encompassing blood circulation, tissue accumulation, cancer cell targeting, endocytosis, endosomal escape, intracellular trafficking to target sites, and therapeutic action, all of which pose limitations to their clinical translation. This underscores the necessity of meticulously considering these biological barriers in the design of cell membrane-mimetic nanocarriers. In this review, we delineate the functions and applications of diverse types of cell membranes in nanocarrier systems. We elaborate on the biological hurdles encountered at each stage of the biomimetic nanoparticle's odyssey to the target, and comprehensively discuss the obstacles imposed by the tumor microenvironment for precise delivery. Subsequently, we systematically review contemporary cell membrane-based strategies aimed at overcoming these multi-level biological barriers, encompassing hybrid cell membrane (HCM) camouflage, tumor microenvironment remodeling, endosomal/lysosomal escape, multidrug resistance (MDR) reversal, optimization of nanoparticle physicochemical properties, and so on. Finally, we outline potential strategies to accelerate the development of cell membrane-inspired precision nanocarriers and discuss the challenges that must be addressed to enhance their clinical applicability. This review serves as a guide for refining the study of cell membrane-mimetic nanosystems in surmounting in vivo delivery barriers, thereby significantly contributing to advancing the development and application of cell membrane-based nanoparticles in cancer delivery.

As technology has evolved in response to pressing human challenges, drug delivery systems (DDSs) have also evolved to overcome complex biological barriers. Particularly, the continuous development of therapeutic strategies has enabled the integration of nanotechnology, leading to the emergence of diverse nanoscale DDSs. Concerns about the potential toxicity of nanomedicines diverted attention to lipid-based nanocarriers (LBNs), regarded as safer and more biocompatible platforms. In this review, the structural evolution of LBNs is categorized into three stages according to the increasing functional complexity required to address biological barriers, providing a framework to understand how designs advanced with physiological demands. This trajectory encompasses emulsions and LBNs, with each stage advanced by strategies such as lipid composition tuning, surface functionalization, biomimetic construction, and hybridization with other platforms. Over a few decades, this transition has described that the progression of LBNs reflects not merely chronological advances but a stepwise evolution of structural adaptations shaped by biological barriers. This analytical perspective is presented through a comprehensive discussion of the structural strategies utilized in recent LBN research. Consequently, structural evolution provides a foundation for refining design approaches in drug delivery and achieving improved therapeutic outcomes.