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PubMed2026

Frontline therapies for adult patients with newly diagnosed Philadelphia chromosome-negative B-cell acute lymphoblastic leukemia: a systematic literature review.

OBJECTIVES: Philadelphia (Ph) chromosome-negative B-cell acute lymphoblastic leukemia (B-ALL) is the most common ALL in adults. Overall survival (OS) with frontline chemotherapy remains poor. Blinatumomab is currently the only targeted agent approved for frontline treatment. METHODS: We systematically reviewed 96 studies (43 interventional, 53 observational) between 2012-2026 evaluating frontline pharmacologic therapy in adults with Ph- B-ALL. RESULTS: Across chemotherapy studies, nearly half of patients relapsed within 3 years, and only 49%-69% survived beyond 3 years. Blinatumomab demonstrated robust and consistent efficacy in first complete response (CR1), supported by 2 randomized controlled trials (RCT) and 16 single-arm trials (SAT). In one RCT, blinatumomab reduced the risk of death by 59% versus chemotherapy alone (HR 0.41) when added to frontline consolidation in minimal residual disease (MRD) negative patients. Median OS reached 41.2 months in a SAT where blinatumomab monotherapy was administered to patients in MRD-positive CR1. SATs showed consistent efficacy outcomes regardless of age, MRD status, or chemotherapy backbone. DISCUSSION: Additional targeted therapies still under investigation have shown mixed results. CONCLUSION: Frontline inotuzumab (±blinatumomab) plus chemotherapy showed promise in older populations, while the efficacy benefit of rituximab was inconclusive. No new safety signals were identified in the frontline setting for targeted therapies.

Humans↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

Intramuscular patient-derived xenografts achieve high engraftment rates in gastric cancer: implications for pharmacodynamic testing and genomic biomarker discovery.

BACKGROUND: Gastric cancer (GC) exhibits marked inter-patient heterogeneity, limiting empirical chemotherapy efficacy. Patient-derived xenograft (PDX) models preserve the molecular features of parental tumors and can serve as pharmacodynamic surrogates, but conventional subcutaneous PDX suffers from low engraftment rates. This study evaluated an optimized intramuscular PDX platform for individualized drug testing in GC and applied whole exome sequencing (WES) for biomarker identification (Clinical trial registry: ChiCTR-OOC-17012731). MATERIALS AND METHODS: Ninety-eight treatment-naive GC patients were enrolled between April 2018 and December 2020. Fresh tumor tissues were engrafted into NCG mice by intramuscular transplantation. Drug efficacy was evaluated using tumor cell necrosis rate and Ki-67 expression. WES was performed on 32 engrafted tumorgrafts to characterize driver mutations in fast- and slow-growing subgroups. RESULTS: An engraftment rate of 71.7% (43/60) was achieved, substantially exceeding rates reported in prior studies. Clinical characteristics were independent of engraftment success and outgrowth time (all p > 0.05). Fast- and slow-growing tumorgrafts diverged in frequently altered genes: KMT2C, APOB, CDK12 and MSH2 predominated in fast-growing grafts, whereas TP53, CHD3 and TET2 were enriched in slow-growing grafts. Slow-growing tumorgrafts correlated with longer progression-free survival (p = 0.02). PDX-guided treatment was associated with improved prognosis. CONCLUSIONS: Intramuscular transplantation into NCG mice yields high engraftment rates for GC PDX. PDX-guided chemotherapy selection is associated with favorable outcomes. Driver mutation divergence between fast- and slow-growing tumorgrafts provides candidate prognostic biomarkers.

Animals↗

PubMed2026

Risk-Benefit of Phase 2 Monotherapy Trials in Adult Solid Cancers: A Systematic Review and Meta-Analysis.

Phase 2 (and phase 1 dose expansion, which we label phase 2 for the purposes of this study) cancer trials are the first direct tests of a new drug's efficacy. Because efficacy evidence is lacking, the therapeutic status of drug administration during ethical review is uncertain. We compared the efficacy and safety of cancer monotherapies in phase 2 with phase 3, where clinical equipoise underwrites a therapeutic status for drug administration. In this systematic review and meta-analysis, we searched Clinicaltrials.gov for phase 2 and 3 investigational monotherapy drug trials in six solid malignancies, with primary completion dates 2015-2020, inclusive. Two independent reviewers completed data extraction. Effects were estimated using an inverse-variance weighted random-effects model meta-analysis of proportions using the R package meta. We analyzed 130 phase 2 and 52 phase 3 trial arms, enrolling 6665 and 18,694 patients. The pooled objective response rate was 7% (95% CI 5%-11%) in phase 2 versus 24% in phase 3 (95% CI 17%-31%; p < 0.0001). The median PFS and OS were shorter in phase 2 compared to phase 3 (3.23 vs. 5.43 months, p < 0.0001; 9.46 vs. 14.44 months, p = 0.0001). The pooled rate of drug-related grade 3-4 adverse events was 30% (95% CI 23%-37%) in phase 2 and 25% (95% CI 19%-32%) in phase 3. Monotherapies delivered in phase 2 cancer trials present diminished risk-benefit compared with phase 3 and align with historic estimates for phase 1. Though there may be exceptions, risks for drug administration in phase 2 should generally be justified by appeals to research rather than therapeutic value.

Humans↗

PubMed2026

Proteomic analysis of cisplatin-induced spermatogenesis defects in mice.

BACKGROUND: Cisplatin is a crucial chemotherapeutic agent used for treating various cancers; however, its excessive use can cause irreversible damage to the reproductive system, and the protein expression profile of cisplatin-induced testicular injury remains unclear. METHODS: Male C57BL/6 mice were treated with cisplatin at various doses, and testes were collected for histological, immunofluorescence, and proteomic analyses. Germ cell loss and apoptosis were assessed using H&E staining, TUNEL assays, and immunofluorescence for LIN28A, SYCP3, MVH, and CDK1. Label-free quantitative proteomics identified differentially expressed proteins, which were analyzed for functional enrichment and protein-protein interactions. RESULTS: We observed that cisplatin treatment led to smaller testes, reduced sperm count, and a significant decrease in the number of spermatocytes and spermatids in mice. Label-free quantitative proteomic analysis revealed that cisplatin significantly reduced the expression of cyclin-dependent kinase 1 (CDK1), a key spermatogenesis regulator, in the testes. Reduction in CDK1 expression is correlated with spermatogenic arrest, particularly in spermatocytes. CONCLUSION: These findings highlight the critical role of CDK1 in cisplatin-induced spermatogenic dysfunction and provide new insights into fertility preservation strategies for patients with cancer undergoing chemotherapy.

Animals↗

PubMed2025

Systematic meta-analysis of the toxicities and side effects of the targeted drug lenvatinib.

BACKGROUND: Lenvatinib, an effective targeted drug for various cancers, has clinical medication safety concerns due to its toxicities and side effects. OBJECTIVE: This study evaluated lenvatinib-induced any adverse events (any AEs) and nine aspects: vascular toxicities related to the circulatory system (vascular toxicities, blood system, and heart), toxicities of the skin and its appendages (skin/subcutaneous tissue and taste system), toxicities of the respiratory system (respiratory, thoracic, and mediastinal and respiratory tract), toxicities of the nervous system (nervous system and general), toxicities of the digestive system (gastrointestinal and liver), toxicities of the urinary system, toxicities of the endocrine and metabolic system (endocrine and metabolism/nutrition), toxicities of the musculoskeletal system, and other severe toxicities. Toxicities and side effects were stratified by severity into any and ≥3 grades for analysis. PATIENTS/MATERIALS AND METHODS: Multiple databases were searched for lenvatinib cancer clinical studies (cohort studies and randomized controlled trials) from inception to December 31, 2024; toxicity and side effect data were extracted and analyzed. RESULTS: Nine high-quality studies were included, showing that lenvatinib is effective in cancers but has notable toxicities. Taking hypertension as an example, for any grade, the risk ratio (RR) was 2.34 with a 95% confidence interval (CI) of [2.09, 2.62], a Z-value of 14.74, and a P-value <0.00001; for grade ≥3, the RR was 2.60 with a 95% CI of [2.21, 3.06], a Z-value of 11.44, and a P-value <0.00001. CONCLUSION: Lenvatinib is effective for cancer but toxic, and this study supports its rational clinical use.

Humans↗