Medicine and Pharmacology

Abstract: Background/Objectives: Prostate cancer remains one of the leading causes of cancer-related morbidity and mortality among men worldwide, highlighting the need for more effective therapeutic strategies. MicroRNAs (miRNAs), small non-coding RNAs that regulate post-transcriptional gene expression, have emerged as promising therapeutic targets because they simultaneously modulate multiple signaling pathways involved in tumor progression, metastasis, androgen receptor signaling, and treatment resistance. Methods: This narrative review synthesizes current evidence on miRNA-based therapeutic strategies for prostate cancer, including miRNA replacement therapy, inhibition of oncogenic miRNAs, and emerging delivery approaches. Results: Particular emphasis is placed on key miRNAs with therapeutic potential, including miR-34a, miR-145, miR-205, miR-146a, miR-141, miR-21, miR-221/222, miR-375, and miR-181a, together with their underlying molecular mechanisms and preclinical evidence. In addition, the review discusses the major challenges limiting clinical translation, including context-dependent miRNA biology, efficient delivery, and safety considerations. Finally, future perspectives on biomarker-guided patient selection, optimized delivery technologies, and combination therapeutic strategies are highlighted to support the development of clinically applicable miRNA-based therapies. Conclusions: Overall, miRNA-based therapeutics represent a promising complementary approach for precision medicine in prostate cancer, although further translational and clinical validation is required before routine clinical implementation.

Abstract: Breast cancer remains a major cause of cancer-related mortality in Africa, where late-stage diagnosis, limited access to specialised care, and underrepresentation in biomedical research continue to impede improvements in patient outcomes. At the same time, rapid advances in tumour biology, molecular diagnostics, and precision oncology are fundamentally reshaping our understanding of breast cancer. This review examines recent developments in breast cancer research through the interconnected lenses of tumour genomics, epigenetics, the tumour microenvironment, immunometabolism, environmental influences, and systems biology, highlighting how these biological insights are driving innovations in diagnostics and targeted therapeutics. We further discuss emerging technologies, including multi-omics, liquid biopsy, artificial intelligence, and patient-derived models, and consider their potential to advance precision oncology. Importantly, we evaluate these advances within the African context, where limited molecular data, restricted access to diagnostic infrastructure, and resource constraints continue to challenge clinical implementation. We argue that improving outcomes across the continent will require more than the adoption of emerging technologies; it will depend on generating African-relevant biological evidence, expanding representation in genomic research, and integrating molecular, clinical, and environmental data to develop equitable, context-specific precision medicine strategies. Such an approach offers the potential to transform breast cancer management while reducing longstanding disparities in cancer care across Africa.

Abstract: Gynecologic cancers remain a major cause of cancer-related morbidity and mortality worldwide despite significant advances in surgery, chemotherapy, radiotherapy, tar-geted therapies, and immunotherapy. Signal Transducer and Activator of Transcription 3 (STAT3) is among the most consistently activated signaling pathways across cervical, ovarian and endometrial cancers, where it contributes to malignant transformation, disease progression, metastatic dissemination and therapeutic resistance. Traditionally, STAT3 oncogenic activity has been attributed to tumor-intrinsic functions, including regulation of proliferation, survival, angiogenesis and stemness. However, growing evidence indicates that STAT3 also participates in dynamic interactions between ma-lignant cells and the tumor microenvironment (TME), integrating inflammatory, meta-bolic and stromal signals that collectively shape disease progression. Rather than func-tioning as an isolated pathway, STAT3 operates within an interconnected regulatory network involving cytokines, hypoxia, metabolic intermediates, stromal cells and im-mune populations. Persistent STAT3 activation contributes to an immunosuppressive microenvironment by influencing macrophage polarization, myeloid-derived suppressor cell expansion, dendritic cell dysfunction, regulatory T-cell accumulation and impaired cytotoxic lymphocyte activity. Simultaneously, metabolic alterations characteristic of gynecologic malignancies — including enhanced glycolysis, lactate accumulation and hypoxia — further reinforce STAT3-dependent signaling across cellular compartments. In this review, we discuss STAT3 as a signaling node linking tumor metabolism with immune regulation in gynecologic cancers, summarize its participation in tumor–microenvironment communication, and examine recent advances in STAT3-targeted therapeutic strategies. We further discuss how a broader understanding of STAT3 biology supports biomarker-guided combination therapies and highlights key challenges lim-iting clinical translation, including the absence of validated predictive biomarkers and the need for improved patient stratification.

Abstract: Tumors of the spine and spinal cord, including primary and metastatic vertebral tumors, intramedullary gliomas, and refractory intradural lesions, are challenging to treat because curative local therapy is limited by the eloquent, nonregenerating neural tissue surrounding them. Oncolytic virotherapy may offer a rational alternative by combining tumor-selective oncolysis with the induction of systemic antitumor immunity, while sparing normal neural cells. This review summarizes the current field of oncolytic viruses, including adenovirus, herpes simplex virus, reovirus, and others, in the context of spinal and spinal cord tumors. Clinical data in the spine remain scarce; however, the rationale is based on histological evidence from sarcomas and other tumors, extensive glioma experience, including diffuse intrinsic pontine glioma, and preclinical activity in nerve sheath and meningioma models. We discuss the telomerase-specific oncolytic adenovirus OBP-301 and its derivatives, whose hTERT-driven replication provides histology-agnostic tumor selectivity, while sparing the telomerase-silent spinal cord. We also discuss delivery and safety within the confined spinal canal, combination strategies, and future directions, such as extracellular vesicle–mediated delivery and biomarker-guided patient selection. Overall, virotherapy is a promising modality for these therapeutically challenging tumors.

Abstract: Cancer classification is important in biomedical research because it can support diagnosis, disease stage classification, and treatment planning. A classification method is even more valuable for practical purposes if it is based on noninvasively or less invasively obtained features instead of invasive biopsies. In this study, machine learning algorithms were applied to two biomedical datasets for cancer classification and to examine how the structure of the data affects classifier performance. The first dataset is the Breast Tissue dataset, which represents a low-dimensional classification problem with 106 observations and 9 predictors. The second dataset is an osteosarcoma DNA methylation dataset, which represents a high-dimensional classification problem with about 480,000 CpG features and 15 samples. Logistic Regression, Support Vector Machine, Random Forest, and K-Nearest Neighbors were applied and compared using accuracy, precision, recall, and F1-score. Principal Component Analysis was used to reduce the dimension of the DNA methylation dataset before classification. The results showed that the machine learning methods performed more reliably in the Breast Tissue dataset. Random Forest and Support Vector Machine had the highest accuracy of 0.7895, while K-Nearest Neighbors had the lowest performance. For the DNA methylation dataset, the model performance was not stable across the different train-test splits. Even after Principal Component Analysis, the results changed depending on how the data were divided and how many principal components were used. This shows that high-dimensional biomedical data with small sample sizes can lead to unstable model performance. Overall, this study shows that machine learning is effective in cancer classification, but the results obtained must be interpreted and adopted carefully, keeping in mind the limitations of such algorithms under certain circumstances, especially when the number of features is much larger than the number of samples.

Abstract: Background: Microsatellite instability-high (MSI-H) and deficient mismatch repair (dMMR) define a molecular subtype of colorectal cancer (CRC) and predict benefit from immune checkpoint inhibition. Clinically, MSI/MMR assessment may yield discordant results across assays, anatomic sites, or time points. A challenging scenario occurs when tissue analysis identifies microsatellite-stable (MSS) or mismatch repair-proficient (pMMR) CRC, whereas circulating tumor DNA (ctDNA) analysis indicates MSI-H- This review evaluates evidence for MSI/MMR heterogeneity and subclonality in CRC. Methods: We reviewed literature on spatial, temporal and subclonal MSI/MMR heterogeneity across human cancers, focusing on CRC. Explanations for tissue-plasma and tissue-tissue dis-cordance, including assay limitations, sampling bias, lesions misattribution, biological evolution, and treatment-related selection, were assessed. Results: Although discordance more commonly reflects assay limitations, sampling bias, or profiling of different lesions, increasing evidence supports genuine biological heterogeneity. Distinct tumor regions max show retained MMR protein expression in one area and regional loss with MSI in another. Noncanonical MMR defects, epigenetic heterogeneity, post-treatment evolution, adaptive mutator-state, and immune selection may also generate dynamic or subclonal instability. Therapeutic relevance may depend not simply on MSI detection, but on whether the unstable clone is sufficiently dominant to generate broadly shared neoanti-gens across the disease burden. Conclusions: MSI/MMR discordance requires careful in-terpretation and should not automatically be considered as true biological heterogeneity. Nevertheless, genuine subclonality occurs in CRC and other cancers and may affect re-sponsiveness to immune checkpoint inhibition. Integrated tissue, plasma, spatial ad lon-gitudinal analyses may improve treatment decisions and biomarker development.

Abstract: Why cancer develops remains one of the central unsolved problems of biology. The Eco-Evolutionary Ground-State Theory of Cancer proposes that malignant transformation results from the conditional reactivation of an ancient ecological survival system whose evolutionary origins extend deep into early eukaryotic evolution. The theory reconstructs approximately one billion years of cancer genome evolution. It proposes that the common ancestor of Amoebozoa, Metazoa, and Fungi (AMF) evolved adaptive regulatory programs enabling survival under fluctuating ecological conditions, particularly changing oxygen availability. Rather than disappearing during the evolution of multicellularity, these programs became integrated into the metazoan genome as an evolutionarily conserved ancestral genomic compartment that normally remains epigenetically suppressed. Malignant transformation is initiated when an irreversibly damaged self-renewing host cell escapes apoptosis, enters reparative senescence, and undergoes unicellularization through reactivation of this ancestral genomic compartment. This transition establishes the eco-evolutionary stemgermline, which functions as the primary regulatory system governing carcinogenesis, tumor progression, cellular plasticity, genome reconstruction, metastatic dissemination, and therapeutic resistance. The genomic instability and phenotypic heterogeneity of malignant tumors are interpreted as downstream consequences of this hierarchical organization rather than its primary cause. The theory further proposes that recurrent unicellularization originally evolved as an adaptive mechanism during the transition to multicellularity but subsequently became transformed through host co-evolution into a parasite-like cellular system. By integrating genome evolution, stemgermline biology, oxygen ecology, and host–parasite co-evolution, the Eco-Evolutionary Ground-State Theory provides a unified evolutionary explanation for both the origin of cancer and the remarkable biological properties that characterize malignant disease.

Abstract: Most patient safety events in radiation therapy originate in treatment planning, and quality assurance (QA) checklists are widely deployed to mitigate them; however, these tools are rarely subjected to formal human factors evaluation before clinical release. Building on our prior work demonstrating suboptimal usability of an institutional dosimetry QA checklist (DQC) and its participatory, theory-driven redesign, this study evaluated an enhanced DQC using Borycki and Kushniruk’s multi-phase, multi-method usability evaluation framework, which integrates cognitive and socio-technical perspectives to create a “safety net” against usability problems and technology-induced errors. Three sequential phases were conducted at an academic medical center: (1) rapid think-aloud usability testing with two cohorts of dosimetrists and physicists (n = 10) separated by an improvement cycle; (2) remote simulation-based testing with dosimetrists (n = 7) using ten high-fidelity synthetic treatment plans with embedded errors; and (3) six weeks of near-live testing with dosimetrists, physicists, and trainees (n = 15–21) with weekly iterative refinement. Reported usability, usefulness, and safety issues decreased by 49% between think-aloud cohorts, and perceived usability met recommended standards (System Usability Scale > 80). Simulation-based testing was feasible, and usability and performance differed significantly between easy and hard plans. Near-live testing surfaced predominantly deeper usefulness and safety issues (77% of 142 codes) and achieved adoption rates of 49–67%. The framework provided complementary, progressively deeper insights and readied the enhanced DQC for clinical implementation.

Abstract: The rapid proliferation of digital pathology has created an urgent need for integrated, scalable, and secure platforms capable of supporting the full lifecycle of whole-slide image (WSI) analysis — from quality assessment through collaborative annotation to AI model deployment. Existing tools address these requirements in isolation, creating fragmented workflows that impede clinical adoption and AI development. Here we present A!Path, a modular ecosystem comprising three synergistic components: (1) A!magQC, a fully automated AI-assisted quality control pipeline assessing five image quality metrics across H&E and multiplex fluorescence modalities; (2) A!HistoClouds, a unified annotation and inference platform that combines cloud-based scalability with local server flexibility, implementing a three-phase closed-loop pathologist-AI interaction workflows, Segment Anything Model (SAM)-based annotation, multi-user collaborative workflows, integrated AI inference (A!Prostate), and project analytics on a deployable backend (A!Server); and (3) A!Secure, a cryptographic security layer for WSI protection, providing application-layer encryption, policy-based access control, streaming tile decryption, and format-aware protection of compressed, pyramid-structured pathology images. A!HistoClouds is deployable on both cloud infrastructure and institutional local servers, enabling organizations to select the deployment model best suited to their data governance requirements without sacrificing platform capability. Validation across a cohort of 302 prostate tissue specimens demonstrated that A!magQC achieved greater than 95% agreement with expert visual quality assessment, while A!Secure-protected WSI regions yielded a low PSNR of 7.42 dB and SSIM of 0.0289 relative to the original images, indicating strong visual obfuscation of diagnostically relevant content. A!Path provides a coherent, deployment-flexible foundation for clinical diagnostic AI development and multi-centre digital pathology collaboration. Conceived as a coordinated data-infrastructure ecosystem rather than a set of isolated tools, A!Path reframes pathology data as an actively governed asset — standardised, clinically annotated, and securely shareable — providing the foundation for trusted multi-institution collaboration under initiatives such as the AI in Digital Pathology (AiDP) programme.

Abstract:

Background: Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, with lymph node metastasis (LNM) being a key predictor of recurrence and poor prognosis. Preoperative detection of LNM remains challenging due to the limitations of imaging modalities, leading to inadequate surgical resection in 20-30% of patients. While immune checkpoint molecules have been implicated in PTC progression, the heterogeneity of CD8+ T cell exhaustion subsets and their specific association with LNM remain poorly defined. Herein, we aimed to characterize the distinct immune landscape of PTC prone to LNM, with a focus on terminal immune exhaustion, to improve risk stratification and therapeutic strategies. Methods: Fresh PTC tissues from 40 patients (22 LNM-positive, 18 LNM-negative) were analyzed by flow cytometry (FCM) to quantify immune cell subsets, inflammatory cytokines, and chemokines. Immunohistochemistry (IHC) validated CD45+ immune cell infiltration. Transcriptomic and clinical data from 448 PTC patients in The Cancer Genome Atlas (TCGA-PTC) cohort were used for bioinformatic validation, including Gene Set Variation Analysis (GSVA) of terminal exhaustion gene signatures. Results: LNM-positive PTC exhibited a unique inflammatory milieu with significantly elevated IL-6, IL-1ra, CCL5, and IL-9 levels (all p<0.05) in tumor interstitial fluid. FCM analysis revealed that LNM-positive PTC had increased infiltration of total CD45+ immune cells, CD3+ T cells, and CD3+CD8+ T cells (all p<0.05). Critically, terminally exhausted PD-1^hiTIM-3⁺ CD8+ T cells were significantly enriched in LNM-positive PTC (p=0.022) and positively correlated with extrathyroidal extension (p=0.044). Additionally, LNM risk was associated with increased CD4+ regulatory T (Treg) cell frequency (p=0.023) and elevated CTLA-4 expression on CD4+ T cells (p=0.047). In TCGA-PTC validation, the terminal exhaustion gene signature was predominantly enriched in LNM-positive (p<0.0001) and advanced-stage PTC (p<0.001), and strongly correlated with BRAF V600E mutation (p<0.0001)—the most common oncogenic driver in aggressive PTC. Conclusion: Our findings identify a terminal immune exhaustion phenotype (characterized by PD-1^hiTIM-3⁺ CD8+ T cells and Treg enrichment) as a key feature of LNM-prone PTC. This phenotype is conserved across clinical samples and TCGA datasets, linking BRAF V600E mutation to immune suppression and metastatic potential. These insights provide a novel immune-based biomarker for LNM risk stratification and support the potential of combining anti-PD-1/TIM-3 therapy with BRAF inhibitors for high-risk PTC.

Abstract: Chronic psychological stress is common among patients with breast cancer and has been linked to poorer outcomes, yet how it weakens antitumor immunity is still incompletely defined. Stress acts through two neuroendocrine arms. The sympathetic nervous system releases catecholamines that signal via β-adrenergic receptors, and the hypothalamic–pituitary–adrenal axis releases glucocorticoids that signal via the glucocorticoid receptor. These arms are usually studied apart. Integrating mechanistic, preclinical, and clinical evidence, we argue that in breast cancer they converge on one immunological endpoint, an exhausted CD8⁺ T cell and natural killer cell phenotype with high inhibitory-receptor expression, and that they reinforce each other through a feed-forward loop in which glucocorticoids sustain catecholaminergic tone. Stress hormones therefore behave as a convergent, druggable neuroendocrine checkpoint. The framework explains why single-arm interventions such as β-blockers or glucocorticoid receptor antagonists have given inconsistent results, and it predicts that co-targeting both arms together with behavioral stress reduction could potentiate immune checkpoint blockade. We assess the supporting evidence, address the paradox that glucocorticoids remain essential for managing immunotherapy toxicity, and set out the models, biomarkers, and trial designs needed to test whether easing the neuroendocrine stress burden restores durable antitumor immunity in breast cancer.

Abstract: Background/Objectives: Cadherin-16 (CDH16, Ksp-cadherin) possesses unique seven extracellular cadherin repeats, and its expression is restricted to normal kidney epithelium. CDH16 is downregulated in renal cell carcinoma (RCC) and is associated with poor prognosis. Therefore, developing mAbs that specifically recognize cell-surface CDH16 is essential for tumor diagnosis and for isolating CDH16-positive renal epithelial cells. Methods: Anti-human CDH16 mAbs (designated as Ca₁₆Mabs) were developed by immunizing mice with CDH16-overexpressed tumor cells, followed by a high-throughput flow cytometry-based screening. Results: Among the 58 established Ca₁₆Mabs, a clone, Ca₁₆Mab-56 (IgG₁, κ), specifically recognized CDH16-overexpressed Chinese hamster ovary-K1 (CHO/CDH16) cells with no detectable cross-reactivity to 21 other CDHs in flow cytometry. Ca₁₆Mab-56 also detected endogenous CDH16 in human RCC cell lines (OS-RC-2 and KMRC-20) and normal kidney epithelial cell lines. The dissociation constant (K_D) values of Ca₁₆Mab-56 for CHO/CDH16 and OS-RC-2 were determined as 6.5 × 10⁻⁹ M and 1.2 × 10⁻⁹ M, respectively. Furthermore, Ca₁₆Mab-56 detected endogenous CDH16 by Western blotting and showed potent staining in normal kidney tubular epithelium and clear membranous staining in renal cell carcinoma in immunohistochemistry. Conclusion: Ca₁₆Mab-56 is a versatile tool for detecting CDH16 and has potential for tumor diagnosis.

Abstract: Background/Objectives. Systemic inflammatory responses influence treatment response and oncological outcomes in patients with cancer. Growing evidence indicates that the inflammatory burden index (IBI) serves as a reliable prognostic indicator across various malignancies. However, the clinical significance of the peri-treatment inflammatory status in patients with RC undergoing preoperative chemoradiotherapy (CRT) remains unclear. Methods. We assessed the pre- and post-treatment IBI in 97 patients with rectal cancer (RC) who received preoperative CRT followed by total mesorectal excision at our institution. Results. Although no significant changes were observed in the pre- or post-CRT IBI and no associations were found with most clinicopathological factors, survival analysis revealed that a high pre-CRT IBI was significantly associated with shorter overall survival (OS) and disease-free survival (DFS). Multivariable analysis revealed that a high pre-CRT IBI and pathological lymph node metastasis remained independent prognostic factors for both outcomes. Subgroup analysis demonstrated that the prognostic value of the peri-treatment IBI differed according to the ypN status, with the pre-CRT IBI showing particularly strong prognostic performance in patients without pathological lymph node metastasis (ypN−). Conclusion. Pre-treatment assessment of the IBI may improve risk stratification in patients with RC undergoing preoperative CRT followed by curative resection.

Abstract: Clinical outcomes for brain cancer are often poor because the blood–brain/tumor barrier hinders effective drug delivery to malignant tissue. Glioblastoma, the most common primary brain malignancy in adults, has an average survival of approximately fourteen months [1]. Here, we discuss novel strategies that our research group and others are developing to deliver chemotherapy to the brain via the nasal cavity. Although significant hurdles remain, intranasal delivery holds substantial promise for improving outcomes for patients with brain cancer. Intranasal delivery is non‑invasive, permits repeated dosing, and has been shown to enable direct nose‑to‑brain transport that bypasses the blood–brain barrier. Challenges such as accurately targeting drugs to the appropriate region of the nasal cavity at therapeutically relevant doses, while maintaining reproducibility, make this cutting-edge approach a regulatory challenge. The prolonged path to clinical translation discourages many researchers from pursuing this potentially life‑saving strategy. Nevertheless, preclinical studies demonstrate that intranasal delivery can achieve up to ten‑fold higher concentrations of select drugs in the brain [2]. Cancer chemotherapeutics span a wide range of molecular formats, from small molecules to 150‑kilodalton antibodies. Accordingly, delivery strategies must be carefully matched to the molecular properties of each therapeutic. Here, we focus on the intranasal delivery of small‑molecule inhibitors using nanomaterial‑based platforms, including aerosols, lipids, gold nanoparticles, gels, emulsions, fibers, and their combinations. Ultimately, we hope that intranasal delivery approaches will be translated to provide patients with better therapeutic outcomes.

Abstract: Breast cancer relapse in bone is a significant clinical problem that is experienced in ~70-80% of patients with late-stage breast cancer. This condition commonly occurs 5-10+ years following surgical removal of the primary tumor. The long latency seen prior to relapse in bone is a result of tumor cell dormancy. Once disseminated to the bone, tumor cell interaction with the bone metastatic niche (endosteal niche and endovascular cells) maintains cells in a dormant state until changes to the local environment activate the niche to support outgrowth. Amassing evidence suggests that cytokines are key regulators of the bone metastatic niche, controlling bone homing and metastatic outgrowth. Pro-inflammatory cytokines including IL-1β, IL-6, IL-8, TGFβ and RANKL play crucial roles in attracting tumor cells to bone. Furthermore, these cytokines act in conjunction with IFN, VEGF, TGF, PTHrP, FGF, OPG and various chemokines to regulate expansion of the niche, facilitating tumor cell escape from dormancy and promoting the “vicious cycle of bone metastasis”. Here, we review the current literature to provide an up to date understanding of how interactions between cytokine signalling cascades regulate the bone metastatic niches to promote homing, dormancy or metastatic outgrowth of breast cancers.

Abstract: Targeted inhibition of the MAPK pathway using BRAF inhibitors (BRAFi) represents a cornerstone of treatment for BRAFV600E-mutant melanoma. However, the rapid emergence of drug resistance remains a major clinical challenge. Mounting evidence indicates that therapy resistance is driven by both phenotypic plasticity and metabolic reprogramming. In this study, we investigated the molecular, phenotypic, and metabolic adaptations underlying acquired resistance to the BRAFi GSK2118436 in A375 melanoma cells. BRAFi-resistant cells (A375-R) displayed cross-resistance to additional BRAFi and MEK inhibitors and clear features of epithelial–mesenchymal transition (EMT), including E-cadherin decreased, vimentin increased, and inhibitor dependent’s spheroid compaction. Metabolic profiling suggests a shift toward mitochondrial oxidative phosphorylation (OXPHOS) dependency. Among multiple metabolic modulators evaluated, inhibitors of mitochondrial respiration—particularly metformin and antimycin A—selectively impaired viability, clonogenicity, and 3D growth of resistant cells. Importantly, while simultaneous BRAFi–metformin combination produced mostly antagonist effects, a sequential regimen (BRAFi followed by metformin) elicited additive/synergistic cytotoxicity in both 2D and 3D models. Collectively, these findings show that BRAFi resistance is driven by coordinated EMT and metabolic rewiring toward OXPHOS dependency and identify sequential metabolic targeting as an effective strategy to overcome therapeutic resistance in melanoma.

Abstract: Structured Abstract Background Actionable oncogenic gene fusions involving ALK, ROS1, RET, NTRK, and NRG1 define distinct molecular subsets of advanced non-small cell lung cancer (NSCLC) that derive substantial benefit from fusion-directed targeted therapies. Although pivotal clinical trials have demonstrated impressive efficacy, comparative real-world outcomes across multiple actionable fusion subtypes remain limited. Methods We conducted a retrospective cohort study of patients with advanced NSCLC harboring actionable gene fusions who received fusion-directed targeted therapy within Memorial Healthcare System. Eligible patients were diagnosed between May 14, 2014, and October 10, 2025, with follow-up through April 24, 2026. Comprehensive molecular profiling was performed using Tempus, Caris Life Sciences, and Guardant360. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan–Meier method. Median follow-up was estimated using the reverse Kaplan–Meier method, and exploratory Cox proportional hazards models evaluated associations between treatment line and survival outcomes. Results Sixty-eight patients met the eligibility criteria, including 34 (50.0%) with ALK, 15 (22.1%) with ROS1, 13 (19.1%) with RET, 4 (5.9%) with NTRK, and 2 (2.9%) with NRG1 fusions. The median age was 62 years; 58.8% were female and 54.4% were never-smokers. Median follow-up was 43.1 months (95% CI, 24.4–50.0). Median PFS was 44.8 months (95% CI, 17.1 months to not estimable), whereas median OS was not reached. Patients who received targeted therapy in the first-line setting had longer PFS than those treated in later lines (HR, 2.16; 95% CI, 1.05–4.44; P = .036), although this exploratory association should be interpreted cautiously because treatment line was not randomized. PFS and OS did not differ significantly among the major fusion subtypes (ALK, ROS1, and RET). Survival outcomes were broadly consistent with those reported in landmark clinical trials, providing supportive real-world evidence for the effectiveness of fusion-directed targeted therapies. Conclusions In this retrospective health-system cohort, patients with advanced NSCLC harboring actionable gene fusions experienced durable disease control with fusion-directed targeted therapy. Real-world survival outcomes were broadly consistent with those reported in landmark clinical trials, supporting the effectiveness of fusion-directed targeted therapies in routine clinical practice and reinforcing the importance of comprehensive genomic profiling to identify patients eligible for precision oncology approaches.

Abstract: Former smokers in lung cancer screening remain at elevated risk for lung cancer despite smoking cessation. We and others have shown that curcumin exhibits anti-inflammatory and antiproliferative effects but is limited by poor bioavailability. However, since curcumin is lipophilic, co-administration with omega-3 fatty acids (ω-3 ω-3 ω-3 FA) represents a mechanistically rational strategy to enhance delivery and target complementary pathways, including STAT3 and NF-κB signaling for lung cancer chemoprevention. Methods: We conducted a randomized, single-blind, placebo-controlled pilot study evaluating curcumin combined with ω-3 FA in high-risk former and current smokers with CT-detected pulmonary nodules. Participants received intervention agents or placebo for 6 months. Primary endpoints included radiologic changes in nodule size, number, and density. Secondary endpoints included safety, adherence, bioavailability, and exploratory biomarker analyses. Correlation analyses of imaging-derived metrics were performed to assess relationships among LDCT parameters. Results: Nineteen participants were enrolled (intervention, n=12; placebo, n=7). No statistically significant between-group differences were observed in primary imaging endpoints. The intervention was well tolerated, with predominantly grade 1 adverse events. Exploratory analyses demonstrated consistent positive correlations among LDCT-derived measures, with clustering of size-based metrics (mean diameter, volume, sum of longest diameters) and density-based parameters. Multidimensional scaling supported this structure, indicating internal coherence among imaging-derived endpoints. Conclusions: Although no statistically significant treatment effect on the image biomarkers was observed, this pilot study demonstrates feasibility challenges and identifies coherent imaging biomarkers that may serve as intermediate endpoints in early-phase chemoprevention trials. These results support further investigation of strategies utilizing agent combinations with enhanced bioavailability and safety and refinement of trial design in high-risk lung cancer patient populations.

Abstract: Background/Objectives: Although dual HER2-targeted neoadjuvant therapy improves pathological complete response (pCR) rates in HER2-positive early breast cancer (EBC), a substantial proportion of patients have residual disease. We evaluated the association between PIK3CA mutations, inflammation–nutritional biomarkers, and pCR. Methods: This retrospective, single-center cohort study included 50 patients with HER2-positive EBC who underwent surgery after neoadjuvant therapy with trastuzumab and pertuzumab. PIK3CA mutations were assessed in diagnostic tumor samples using real-time PCR. Pretreatment HALP, CALLY, CRII, and other inflammation-based indices were calculated. Logistic regression and receiver operating characteristic (ROC) analyses were used to identify determinants of pCR, defined as ypT0/is ypN0. Results: pCR was observed in 32 patients (64.0%), and 15 patients (30.0%) had PIK3CA-mutant tumors. The pCR rate was lower in PIK3CA-mutant than in wild-type tumors (40.0% vs. 74.3%; Pearson’s chi-square p = 0.021; Fisher’s exact p = 0.028). Response did not differ significantly among treatment regimens. The highest pCR rate occurred in hormone receptor (HR)-negative/PIK3CA wild-type tumors (81.3%), whereas the lowest occurred in HR-positive/PIK3CA-mutant tumors (30.0%). CALLY was independently associated with pCR (AUC = 0.755, p = 0.003). LCR (AUC = 0.776, p = 0.001) and CAR (AUC = 0.763, p = 0.002) also showed discriminatory ability, whereas HALP was not associated with response. Conclusions: PIK3CA mutations were associated with lower pCR rates, while inflammation–nutritional indices provided complementary predictive information. This combined molecular and host-related biomarker assessment may offer a more comprehensive approach to baseline response stratification. These findings require confirmation in larger prospective multicenter studies before clinical implementation.

Abstract: Cancer cachexia is a multifactorial systemic syndrome characterized by progressive muscle loss, with or without adipose tissue depletion, that cannot be reversed by conventional nutritional support. It affects cancer patients and is associated with reduced treatment tolerance, impaired physical function, poor quality of life, and increased mortality. The understanding of cachexia has evolved recently, from the perception of a simple nutritional disorder to a complex immune-metabolic syndrome, based on tumor-host interactions, systemic inflammation, metabolic dysregulation, and multi-organ dysfunction. This review summarizes the progression of cachexia research, highlighting key findings involving inflammatory cytokines, proteolytic pathways, mitochondrial dysfunction, and immune dysregulation. The development of therapeutic strategies is examined, from early nutritional and appetite-stimulating interventions to contemporary targeted therapies, including ghrelin receptor agonists, cytokine inhibitors, and anabolic agents. Despite advances in mechanistic understanding, numerous trials targeting single pathways have failed to produce meaningful functional or survival benefits, underscoring the limitations of reductionist approaches. Emerging evidence supports a paradigm shift toward multimodal, biomarker-guided, and patient-centered interventions that address the interconnected biological mechanisms underlying cachexia. Particular emphasis is given to novel immunomodulatory strategies, including agents such as R-ketorolac, which may restore immune homeostasis and target the root causes of cachexia. It is hypothesized that future therapeutic success will likely depend on integrated approaches combining immunological, metabolic, nutritional, and rehabilitative interventions.