Gemcitabine in non-small cell lung cancer

Identification of disulfidptosis-related subgroups and prognostic signatures in lung adenocarcinoma using machine learning and experimental validation

Background

Disulfidptosis is a newly identified variant of cell death characterized by disulfide accumulation, which is independent of ATP depletion. Accordingly, the latent influence of disulfidptosis on the prognosis of lung adenocarcinoma (LUAD) patients and the progression of tumors remains poorly understood.

Methods

We conducted a multifaceted analysis of the transcriptional and genetic modifications in disulfidptosis regulators (DRs) specific to LUAD, followed by an evaluation of their expression configurations to define DR clusters. Harnessing the differentially expressed genes (DEGs) identified from these clusters, we formulated an optimal predictive model by amalgamating 10 distinct machine learning algorithms across 101 unique combinations to compute the disulfidptosis score (DS). Patients were subsequently stratified into high and low DS cohorts based on median DS values. We then performed an exhaustive comparison between these cohorts, focusing on somatic mutations, clinical attributes, tumor microenvironment, and treatment responsiveness. Finally, we empirically validated the biological implications of a critical gene, KYNU, through assays in LUAD cell lines.

Results

We identified two DR clusters and there were great differences in overall survival (OS) and tumor microenvironment. We selected the "Least Absolute Shrinkage and Selection Operator (LASSO) + Random Survival Forest (RFS)" algorithm to develop a DS based on the average C-index across different cohorts. Our model effectively stratified LUAD patients into high- and low-DS subgroups, with this latter demonstrating superior OS, a reduced mutational landscape, enhanced immune status, and increased sensitivity to immunotherapy. Notably, the predictive accuracy of DS outperformed the published LUAD signature and clinical features. Finally, we validated the DS expression using clinical samples and found that inhibiting KYNU suppressed LUAD cells proliferation, invasiveness, and migration in vitro.

Conclusions

The DR-based scoring system that we developed enabled accurate prognostic stratification of LUAD patients and provides important insights into the molecular mechanisms and treatment strategies for LUAD.

Treatment options after first-line immunotherapy in metastatic NSCLC

Introduction: The recent approvals of checkpoint inhibitors as single agents or in combination with chemotherapy with programmed death ligand 1 expression of < or ≥1% have challenged clinicians when it is time to begin a metastatic lung cancer patient in second-line therapy. The advantages given by immunotherapy over conventional chemotherapy such as improved overall survival and a better toxicity profile make the second-line clinical scenario more difficult for a patient who faces a likely inferior regimen as well as toxicity which may significantly impact the quality of life.Areas covered: Options given today by the National Comprehensive Cancer Network are very limited, and essentially, we go back to conventional cytotoxic agents alone or in combination with biological agents if possible. In this article, we discuss the actual treatment available for this difficult scenario and some of the ongoing trials which aim to address this dilemma.Expert commentary: This is an unmet need in lung cancer management; we need a better understanding of the mechanism of resistance to immunotherapy so we can target them once the patient moves to second-line treatment.

The potential of radiolabeled chemotherapeutics in tumor diagnosis: Preliminary investigations with 68 Ga-gemcitabine

Preclinical Research & Development Gemcitabine, a nucleoside analog, is a well-known chemotherapeutic drug that is used either alone or with other agents to treat a wide variety of cancers. The aim of the present work was to evaluate the potential of ⁶⁸ Ga-labeled gemcitabine for its application in positron emission tomography (PET) imaging of tumorous lesions. Gemcitabine was coupled with p-NCS-benzyl-DOTA in order to facilitate radiolabeling with ⁶⁸ Ga. The gemcitabine-p-NCS-benzyl-DOTA was radiolabeled with ⁶⁸ Ga, obtained from a ⁶⁸ Ge/⁶⁸ Ga radionuclide generator. The radiolabeled product was characterized by high performance liquid chromatography (HPLC) and its tumor specificity was evaluated by biodistribution studies in Swiss mice bearing fibrosarcoma tumors. Preliminary bioevaluation study showed good tumor uptake within 1 hr post-administration [2.5% Injected Activity (IA) per g of tumor] with rapid renal clearance (>90% IA) and a high tumor to muscle ratio. ⁶⁸ Ga-gemcitabine may have potential as a PET agent for tumor imaging.

A Practical Application of Value of Information and Prospective Payback of Research to Prioritize Evaluative Research

BACKGROUND AND OBJECTIVES

Efforts to ensure that funded research represents "value for money" have led to increasing calls for the use of analytic methods in research prioritization. A number of analytic approaches have been proposed to assist research funding decisions, the most prominent of which are value of information (VOI) and prospective payback of research (PPoR). Despite the increasing interest in the topic, there are insufficient VOI and PPoR applications on the same case study to contrast their methods and compare their outcomes. We undertook VOI and PPoR analyses to determine the value of conducting 2 proposed research programs. The application served as a vehicle for identifying differences and similarities between the methods, provided insight into the assumptions and practical requirements of undertaking prospective analyses for research prioritization, and highlighted areas for future research.

METHODS

VOI and PPoR were applied to case studies representing proposals for clinical trials in advanced non-small-cell lung cancer and prostate cancer. Decision models were built to synthesize the evidence available prior to the funding decision. VOI (expected value of perfect and sample information) and PPoR (PATHS model) analyses were undertaken using the developed models.

RESULTS AND CONCLUSIONS

VOI and PPoR results agreed in direction, suggesting that the proposed trials would be cost-effective investments. However, results differed in magnitude, largely due to the way each method conceptualizes the possible outcomes of further research and the implementation of research results in practice. Compared with VOI, PPoR is less complex but requires more assumptions. Although the approaches are not free from limitations, they can provide useful input for research funding decisions.

The C-terminal region of Bfl-1 sensitizes non-small cell lung cancer to gemcitabine-induced apoptosis by suppressing NF-κB activity and down-regulating Bfl-1

Gemcitabine is used to treat several cancers including lung cancer. However, tumor cells often escape gemcitabine-induced cell death via various mechanisms, which include modulating bcl-2 family members and NF-κB activation. We previously reported that the C-terminal region of Bfl-1 fused with GFP (BC) is sufficient to induce apoptosis in 293T cells. In the present study, we investigated the anti-tumor effect of combined BC gene therapy and gemcitabine chemotherapy in vitro and in vivo using non-small cell lung cancer cell lines and a xenograft model. Cell lines were resistant to low dose gemcitabine (4-40 ng/ml), which induced NF-κB activation and concomitant up-regulation of Bfl-1 (an NF-κB-regulated anti-apoptotic protein). BC induced the apoptosis of A549 and H157 cells with caspase-3 activation. Furthermore, co-treatment with BC and low dose gemcitabine synergistically and efficiently induced mitochondria-mediated apoptosis in these cells. When administered alone or with low dose gemcitabine, BC suppressed NF-κB activity, inhibited the nuclear translocation of p65/relA, and down-regulated Bfl-1 expression. Furthermore, direct suppression of Bfl-1 by RNA interference sensitized cells to gemcitabine-induced cell death, suggesting that Bfl-1 importantly regulates lung cancer cell sensitivity to gemcitabine. BC and gemcitabine co-treatment also showed a strong anti-tumor effect in a nude mouse/A549 xenograft model. These results suggest that lung cancer cells become resistant to gemcitabine via NF-κB activation and the subsequent overexpression of Bfl-1, and that BC, which has both pro-apoptotic and NF-κB inhibitory effects, could be harnessed as a gene therapy to complement gemcitabine chemotherapy in non-small cell lung cancer.

Antitumor activity of EGFR targeted pH-sensitive immunoliposomes encapsulating gemcitabine in A549 xenograft nude mice

Immunoliposomes directed by monoclonal antibodies are promising vehicles for tumor targeted drug delivery. Development of a long-circulating formulation of pH-sensitive liposomes (PSLs) with epidermal growth factor receptor (EGFR) antibody attached was designed and tested using A549 cells and BALB/c-nu/nu mouse tumor model. PSL formulation was prepared using small unilamellar vesicles of DOPE and CHEMS (6:4 molar ratio) by REV method. The average size and zeta-potential of the formulation measured by dynamic laser-light scattering were approximately 146+/-43.9 nm (PDI=0.09+/-0.02) and -1.77+/-0.03 mV, respectively. A549 cells were xenotransplanted into BALB/c-nu/nu mice and various formulations of gemcitabine (gem), such as in its free form, PSLs or Ab-PSLs, were injected intravenously via a tail vein. The rate of tumor volume increment in Ab-PSLs with gem-treated group was remarkably slower than that of other drug-treated group. The tumor from Ab-PSLs with gem 160 mg/kg-injected group exhibited a markedly lowest account of PCNA labeled cells and had highest TUNEL-positive cells among tested. This suggests that treatment of Ab-PSLs with gem resulted in an increased apoptosis of tumor cells, leading to tumor growth inhibition. These results demonstrate that PSLs provide an efficient and targeted delivery of gemcitabine and may represent a useful new treatment approach for tumors which overexpress the EGFR.