Hemophagocytic lymphohistiocytosis following pembrolizumab and bevacizumab combination therapy for cervical cancer: a case report and systematic review.

BACKGROUND: Programmed cell death protein 1 (PD-1) checkpoint inhibitors such as pembrolizumab are novel therapeutics used to treat various advanced malignancies. Immune-related adverse events are common, among the most serious of these toxicities is hemophagocytic lymphohistiocytosis (HLH), which is a life-threatening disorder of unbridled immune activation but has not been properly established. METHODS: We have procured the first case of hemophagocytic lymphohistiocytosis as an aftermath of treatment with pembrolizumab from the Sir Run Run Shaw Hospital, Zhejiang University, China. In a pursuit to enhance the understanding of this condition, a comprehensive systematic review was performed encompassing all reported instances of ICI-associated Hemophagocytic lymphohistiocytosis within the realms of PubMed and Embase databases. RESULTS: We detail the recovery of a cervical cancer patient with a history of psoriasis who developed HLH after combined pembrolizumab and bevacizumab treatment. Remarkably, tumor lesions exhibited substantial and sustained regression. From an analysis of 52 identified Immune Checkpoint Inhibitor (ICI)-related HLH cases, we discovered that HLH often occurred within the first two treatment cycles and approximately 20% of these patients had a history of autoimmune-related diseases. Despite a 15% mortality rate, the majority of patients experienced positive outcomes. Notably, in instances of recovery from HLH, 80% showed positive tumor outcomes. Even after discontinuation of ICI treatment, tumor control persisted in some cases. CONCLUSION: We identified the first case of HLH caused by ICI treatment in cervical cancer and summarized the possible occurrence factors of these cases, the treatment outcomes of HLH, and the impact on tumor outcomes.

Autophagy in colitis-associated colon cancer: exploring its potential role in reducing initiation and preventing IBD-Related CAC development.

ABBREVIATIONS: A. muciniphila: Akkermansia muciniphila; AIEC: adherent invasive Escherichia coli; AOM/DSS: azoxymethane-dextran sodium sulfate; ATG: autophagy related; BECN1: beclin1, autophagy related; CAC: colitis-associated colon cancer; CCDC50: coiled-coil domain containing 50; CLDN2: claudin 2; CoPEC: colibactin-producing Escherichia coli; CRC: colorectal cancer; DAMPs: danger/damage-associated molecular patterns; DC: dendritic cell; DSS: dextran sulfate sodium; DTP: drug-resistant persistent; ER: endoplasmic reticulum; ERN1/IRE1α: endoplasmic reticulum to nucleus signaling 1; IBD: inflammatory bowel disease; IECs: intestinal epithelial cells; IKK: IkappaB kinase; IL: interleukin; IRGM1: immunity-related GTPase family M member 1; ISC: intestinal stem cell; LPS: lipopolysaccharide; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; MAPK: mitogen-activated protein kinase; MDP: muramyl dipeptide; MELK: maternal embryonic leucine zipper kinase; MHC: major histocompatibility complex; miRNA: microRNA; MTOR: mechanistic target of rapamycin kinase; NLRP3: NLR family, pyrin domain containing 3; NOD2: nucleotide-binding oligomerization domain containing 2; NRBF2: nuclear receptor binding factor 2; PAMPs: pathogen-associated molecular patterns; PI3K: class I phosphoinositide 3-kinase; PtdIns3K: class III phosphatidylinositol 3-kinase; PYCARD/ASC: PYD and CARD domain containing; RALGAPA2/RalGAPα2: Ral GTPase activating protein protein, alpha subunit 2 (catalytic); RIPK2/CARD3: receptor (TNFRSF)-interacting serine-threonine kinase 2; RIPK3: receptor-interacting serine-threonine kinase 3; ROS: reactive oxygen species; sCRC: sporadic colorectal cancer; SMARCA4/BRG1: SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4; SQSTM1: sequestosome 1; STAT3: signal transducer and activator of transcription 3; TNF/TNFA: tumor necrosis factor; ULK1: unc-51 like autophagy activating kinase 1; UPR: unfolded protein response; WT: wild-type.

Exploration and machine learning model development for T2 NSCLC with bronchus infiltration and obstructive pneumonia/atelectasis.

In the 8th edition of the American Joint Committee on Cancer (AJCC) staging system for Non-Small Cell Lung Cancer (NSCLC), tumors exhibiting main bronchial infiltration (MBI) near the carina and those presenting with complete lung obstructive pneumonia/atelectasis (P/ATL) have been reclassified from T3 to T2. Our investigation into the Surveillance, Epidemiology, and End Results (SEER) database, spanning from 2007 to 2015 and adjusted via Propensity Score Matching (PSM) for additional variables, disclosed a notably inferior overall survival (OS) for patients afflicted with these conditions. Specifically, individuals with P/ATL experienced a median OS of 12 months compared to 15 months (p < 0.001). In contrast, MBI patients demonstrated a slightly worse prognosis with a median OS of 22 months versus 23 months (p = 0.037), with both conditions significantly correlated with lymph node metastasis (All p < 0.001). Upon evaluating different treatment approaches for these particular T2 NSCLC variants, while adjusting for other factors, surgery emerged as the optimal therapeutic strategy. We counted those who underwent surgery and found that compared to surgery alone, the MBI/(P/ATL) group experienced a much higher proportion of preoperative induction therapy or postoperative adjuvant therapy than the non-MBI/(P/ATL) group (41.3%/54.7% vs. 36.6%). However, for MBI patients, initial surgery followed by adjuvant treatment or induction therapy succeeded in significantly enhancing prognosis, a benefit that was not replicated for P/ATL patients. Leveraging the XGBoost model for a 5-year survival forecast and treatment determination for P/ATL and MBI patients yielded Area Under the Curve (AUC) scores of 0.853 for P/ATL and 0.814 for MBI, affirming the model's efficacy in prognostication and treatment allocation for these distinct T2 NSCLC categories.

Developing a prognostic model using machine learning for disulfidptosis related lncRNA in lung adenocarcinoma.

Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential implications for advancements in cancer treatments. Although emerging evidence highlights the critical regulatory roles of long non-coding RNAs (lncRNAs) in the pathobiology of lung adenocarcinoma (LUAD), research into lncRNAs specifically associated with disulfidptosis in LUAD, termed disulfidptosis-related lncRNAs (DRLs), remains insufficiently explored. Using The Cancer Genome Atlas (TCGA)-LUAD dataset, we implemented ten machine learning techniques, resulting in 101 distinct model configurations. To assess the predictive accuracy of our model, we employed both the concordance index (C-index) and receiver operating characteristic (ROC) curve analyses. For a deeper understanding of the underlying biological pathways, we referred to the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) for functional enrichment analysis. Moreover, we explored differences in the tumor microenvironment between high-risk and low-risk patient cohorts. Additionally, we thoroughly assessed the prognostic value of the DRLs signatures in predicting treatment outcomes. The Kaplan-Meier (KM) survival analysis demonstrated a significant difference in overall survival (OS) between the high-risk and low-risk cohorts (p < 0.001). The prognostic model showed robust performance, with an area under the ROC curve exceeding 0.75 at one year and maintaining a value above 0.72 in the two and three-year follow-ups. Further research identified variations in tumor mutational burden (TMB) and differential responses to immunotherapies and chemotherapies. Our validation, using three GEO datasets (GSE31210, GSE30219, and GSE50081), revealed that the C-index exceeded 0.67 for GSE31210 and GSE30219. Significant differences in disease-free survival (DFS) and OS were observed across all validation cohorts among different risk groups. The prognostic model offers potential as a molecular biomarker for LUAD prognosis.

A real world analysis of secondary BRAF variations after targeted therapy resistance in driver gene positive NSCLC.

Secondary BRAF variations have been identified as a mechanism of resistance to tyrosine kinase inhibitors (TKIs) in patients with driver gene-positive NSCLC. Nevertheless, there is still a lack of consensus regarding the characteristics and subsequent treatment strategies for these patients. We retrospectively reviewed the medical records of patients with driver gene-positive NSCLC who received TKIs therapy at Zhejiang Cancer Hospital between May 2016 and December 2023. The clinical and genetic characteristics of these patients were assessed, along with the impact of various treatment strategies on survival. This study enrolled 27 patients with advanced NSCLC, in whom BRAF variations occurred at a median time of 28 months after the initiation of targeted therapy. The multivariate accelerated failure time (AFT) model revealed that, compared to chemotherapy-based regimens group, the combined targeted therapy group (p < 0.001) and the combined local treatment group for oligo-progression (p < 0.001) significantly extended patient survival. In contrast, continuing the original signaling pathway's targeted monotherapy was associated with shorter survival (p = 0.034). The median global OS for each treatment group was as follows: chemotherapy-based regimens group, 45 months; combined targeted therapy group, 59 months; combined local treatment group for patients with oligo-progression, 46 months; and targeted monotherapy group, 36 months. Study results indicate that the combination targeted therapy group (including TKIs, BRAF inhibitors, and/or MEK inhibitors) and the localized treatment group are more effective than traditional chemotherapy-based regimens in improving survival. Additionally, continuing targeted monotherapy along the original signaling pathway proves less effective than chemotherapy-based regimens.

Optimizing first-line TKI treatment efficacy in PD-L1-positive EGFR-mutated NSCLC: the impact of antiangiogenic agents.

Background: In individuals receiving treatment with epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs), those exhibiting positive PD-L1 expression might experience reduced progression-free survival (PFS). However, the effects on overall survival (OS) and the determination of efficacious treatment approaches are still not well-defined. Methods: In our retrospective study, we examined data from 193 NSCLC patients with advanced EGFR mutations who received first-line TKI treatments, treated at two centers of Shaw Hospital in Zhejiang, China. This analysis covered a period from 1 January 2016 to 30 April 2023. Results: Patients with PD-L1 positivity exhibited a markedly shorter average PFS (9.5 months versus 17.8 months, P < 0.001) and OS (44.4 months versus 65.7 months, P = 0.016) relative to those without PD-L1 expression. This difference in both PFS and OS remained statistically significant even after adjusting for multiple factors (P < 0.001 for PFS and P = 0.028 for OS). In the PD-L1-positive cohort, introducing combination antiangiogenic significantly extended both PFS (from 9.1 to 25.7 months, P = 0.026) and OS (from 42 to 53.5 months, P = 0.03). Post-first-line TKI therapy, 39.3% of PD-L1-positive patients and 54.5% of PD-L1-negative patients developed the T790M mutation (P = 0.212), with no notable difference in PFS from second-line TKI treatments between the groups. Additionally, subsequent combination therapy with immunotherapy markedly prolonged OS in the PD-L1-positive group. However, for PD-L1-negative patients, neither combination antiangiogenic therapy nor later-line immunotherapy demonstrated significant benefits in PFS or OS. Conclusion: For PD-L1-positive patients, combined antiangiogenic treatments and immunotherapy can significantly improve survival outcomes. In contrast, PD-L1-negative patients show less benefit from these therapies, highlighting the greater efficacy of these treatments in PD-L1-positive individuals.

Revolutionizing T3-4N0-2M0 gastric cancer staging with an innovative pathologic N classification system.

BACKGROUND: The current pathologic N (pN) classification exhibits limitations in the prognostic stratification of patients with pT3-4N0-2M0 gastric cancer (GC). Therefore, this study aimed to develop and validate a new lymph nodal staging method based on the number of examined lymph nodes (ELNs) and lymph node ratio (LNR). METHODS: Data from 7883 patients with pT3-4N0-2M0 GC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and Zhejiang Cancer Provincial Hospital. Optimal cutoff values for ELNs and LNR were determined using X-tile software. Kaplan-Meier methods, Log-rank tests, and Cox regression analyses were employed in this study. Patients were categorized into 3 new pN stages: new pN0 (pN0 with ELNs of >16), new pN1 (pN0 with ELNs of ≤16 or pN1-2 with LNR of ≤0.15), and new pN2 (pN1-2 with LNR of >0.15). The prognostic predictive power of both current and new pN staging was evaluated using the Akaike information criterion (AIC), Bayesian information criterion, concordance index (C-index), and receiver operating characteristic curve. RESULTS: The new pN classification exhibited excellent performance in Kaplan-Meier survival analysis. After adjusting for confounding factors, the new pN staging emerged as an independent prognostic indicator in patients with GC. In the SEER cohort, the new pN staging demonstrated enhanced prognostic prediction accuracy over the American Joint Committee on Cancer pN staging (AIC: 75578.85 vs 75755.06; C-index: 0.642 vs 0.630; P < .001). Similar findings were validated in the Chinese cohort. CONCLUSION: This study developed and validated an improved pN classification for patients with pT3-4N0-2M0 GC. Surgeons should consider ELNs and LNR when assessing postoperative prognosis in patients with GC.