Ke Xu

The prognosis for patients with advanced pancreatic cancer (PC) remains extremely poor, underscoring the critical need to explore and optimize systemic treatment strategies. This study aimed to evaluate the efficacy and safety of combining EGFR monoclonal antibodies (Anti-EGFR-mAb) with gemcitabine-based chemotherapy as a first-line treatment for locally advanced or metastatic PC. A total of 11 studies were included, with a total sample size of 1123 patients with locally advanced or metastatic PC. Meta-analysis results showed that the objective response rate (ORR) for first-line treatment of advanced PC with Anti-EGFR-mAb combined with gemcitabine was 15% (95% CI: 10-22%), and the disease control rate (DCR) was 58% (95% CI: 49-67%). Compared with gemcitabine-based chemotherapy, combination therapy did not improve progression-free time (PFS) (HR = 0.93, 95%CI: 0.81-1.04, p = 0.057) or overall survival (OS) (HR = 0.90, 95%CI: 0.78-1.02, p = 0.04). The incidence of severe adverse events (sAEs) caused by combination therapy was 31% (95% CI: 14-50%). Anti-EGFR-mAb combined with gemcitabine chemotherapy has shown a good efficacy to first-line treatment of advanced PC, it did not provide a significant survival benefit compared to chemotherapy alone. Additionally, combination therapy was associated with a high incidence of AEs, highlighting safety concerns that warrant special attention. PROSPERO (CRD420250652874).

Background and Objective: Small cell lung cancer has a high incidence and mortality rate, frequently metastasizes, and is associated with a poor prognosis. However, traditional prognostic models based on stage alone cannot meet clinical needs. This study aims to establish a clinlabomics‐based, highly accessible prognostic model for small cell lung cancer. Methods: We conducted a multicenter observational retrospective study, enrolling clinical laboratory data of 276 small cell lung cancer patients. The cohort from Sichuan Cancer Hospital comprised a total of 196 samples. Of these, 88 samples were designated as the internal validation set, while 80 samples from an alternate institution were allocated as the external independent validation set. Utilizing the log‐rank test, univariate and multivariate Cox regression analyses, six prognostic indicators were discerned. A nomogram was subsequently developed based on these identified indicators. Results: Through the log‐rank test, univariate and multivariate Cox regression analyses, total protein (TP) (HR = 0.47, p < 0.001), aspartate aminotransferase (AST) (HR = 1.82, p < 0.001), and lymphocyte ratio (Lym ratio) (HR = 0.47, p = 0.005) were identified as laboratory biomarkers related to prognosis from 61 blood‐related laboratory tests, covering routine blood, biochemical, coagulation, and infectious disease markers, while age, stage, and smoking were identified as clinical independent prognostic factors. A nomogram was developed based on these six indicators. The AUC of time‐independent ROC for 2‐ and 3‐year overall survival (OS) was 0.74, 0.74 in the training cohort, and 0.64, 0.74 in the validation cohort, respectively. The novel nomogram accurately predicted the prognosis for two independent cohorts with p values < 0.001 and performed risk adjustment, which classified patients with different OS at the same extensive stage (ES) or limited‐stage (LS). Conclusions: The clinlabomics‐based nomogram helps to more effectively predict the prognosis of small cell lung cancer by leveraging blood laboratory data.

Background: Pathologically, clear cell renal cell carcinoma (ccRCC) is the most common type of renal carcinoma, with high heterogeneity and poor prognosis. There is increasing evidence that alternative splicing (AS) is involved in tumor evolution and tumor immune microenvironment (TIME). However, studies on the exploration of AS events and TIME in ccRCC are still few but needed. Methods: The transcriptional data and clinicopathological information of patients with ccRCC in The Cancer Genome Atlas (TCGA) database were extracted completely. Patients were grouped according to the ESTIMATE algorithm and differentially expressed AS events (DEASs) were identified. The relationship between AS events and features of TIME were investigated by functional enrichment analysis and unsupervised consensus analysis. Finally, hub splicing factors (SFs) was identified by the regulatory network of survival-related AS events and intersection SFs, and its biological function was further verified in vitro. Results: In total, the data of 515 patients with ccRCC were extracted and analyzed. Patients with low immune-score presented longer overall survival (OS) than high immune-score. 861 AS events were identified as DEASs, and they were enriched in immune-related pathways. 3 AS-based clusters were identified and found to have different prognoses and unique immune features. Finally, MBNL1 was identified as a hub SF, and it was shown to inhibit proliferation and metastasis, promote apoptosis, and block cells in G2/M phase in 786O and A498 cells. Mechanistically, MBNL1 regulates QKI expression through AS. Conclusion: The prognostic risk model constructed base on immune-related AS events has good predictive ability for ccRCC. The hub SF MBNL1 identied in the present study could inhibit the progression of ccRCC. This effect is likely due to the regulation of QKI expression through AS.

This study aimed to systematically analyze the efficacy and toxicity of lurbinectedin as a second-line or subsequent treatment for extensive-stage small cell lung cancer (ES-SCLC). Candidate studies were identified in PubMed, Embase, Cochrane Library, ClinicalTrials.gov, CNKI, and Wanfang databases up to 1 May 2024. Objective remission rate (ORR), disease control rate (DCR), duration of response (DOR), progression-free survival (PFS), overall survival (OS), and adverse events (AEs) were extracted, respectively. The efficacy and toxicity of lurbinectedin in ES-SCLC were analyzed by meta-analysis. Six eligible prospective studies were included in this meta-analysis, including 536 patients with ES-SCLC who received second-line or subsequent treatment. In pooled analysis, the ORR of lurbinectedin was 35% (95% confidence interval [CI] 29–41), DCR was 67% (95%CI 58–76), DOR was 5.33 months (95%CI 4.51-6.16), PFS was 3.38 months (95%CI 2.59-4.17), and OS was 7.49 months (95%CI 5.11–9.87). The incidence of AEs and severe adverse events (SAEs) was 92% (95%CI 78–100) and 37% (95%CI 19–57), respectively. The most common AEs were leukopenia, neutropenia, anemia, and thrombocytopenia, with incidences of 81% (68–91), 74% (57–88), 73% (35–98) and 57% (46–68), respectively. As a promising alternative for second-line treatment for ES-SCLC, lurbinectedin has a certain level of efficacy and a favorable safety profile. The integration of lurbinectedin with other therapeutic modalities presents an emerging area warranting further investigation.

Background: COL10A1 expression was up-regulated and could promote tumor development in pancreatic cancer. As a secreted protein, plasma COL10A1 level was proven to have certain diagnostic efficacy in gastric cancer, breast cancer, and colorectal cancer. It is still unknown whether it has a biomarker role for pancreatic cancer. Aim: To explore and analyze the diagnostic and prognostic value of plasma COL10A1 level in pancreatic ductal adenocarcinoma (PDAC). Method: The RNA-seq dataset of PDAC from The Cancer Genome Atlas (TCGA) and six expression profiling microarray datasets from Gene Expression Omnibus (GEO) were downloaded to analyze the expression of COL10A1 in tissues. Thirty-six patients with PDAC and eighteen healthy volunteers were enrolled to measure COL10A1 levels in tissues and plasmas, and the relationship between clinical characteristics and the COL10A1 levels was analyzed. The diagnostic and prognostic efficacy of plasma COL10A1 levels were calculated. Results: Aspects of COL10A1 expression level in tissues, COL10A1 expression was significantly higher in PDAC tissue than adjacent normal tissue. The expression of COL10A1 was correlated with T, M, and AJCC stages. Patients with high COL10A1 expression had worse recurrence-free survival (RFS) and overall survival (OS) than those with low expression. Aspects of COL10A1 expression levels in plasma, its diagnostic area under the curve (AUC) for PDAC was 0.926 (95% CI 0.853– 0.999), diagnostic sensitivity was 81% (95% CI 64– 92%), and specificity was 100% (95% CI 81– 100%). The time-dependent AUCs at 1-year and 3-year were 0.71 (95% CI 0.51– 0.90) and 0.74 (95% CI 0.48– 1.00), respectively. Conclusion: In PDAC, plasma COL10A1 levels showed certain diagnostic and prognostic efficacy. COL10A1 may be a diagnostic and prognostic biomarker for PDAC and play a role in liquid biopsy of this disease.

Background: Breast cancer is a prevalent disease that has a dismal prognosis for patients and a bad outlook for treatments. Ubiquitination is a reversible biological process that regulates protein production and degradation, as well as plays a vital role in protein transport, localization, and biological activity. Methods: We obtained the breast cancer patient sample data and used a machine learning technique to create a novel index called Deubiquitinating enzyme related index (DUBRI) by gathering genes associated to deubiquitinating enzymes. Based on DUBRI, we systematically analyze patients’ prognosis, clinical characteristics, tumor immune microenvironment, chemotherapy response and immunotherapy response. Finally, the function of OTUB2 was explored in breast cancer cells. Results: DUBRI, which consists of five deubiquitinating enzyme genes (OTUB2, USP41, MINDY2, YOD1, and PSMD7), is a reliable predictor of survival in breast cancer patients. We found that the high DUBRI group presented higher levels of immune cell infiltration. We performed molecular docking prediction of core target proteins in deubiquitinating enzymes. In vitro experiments verified that knockdown of OTUB2 could inhibit the proliferation and migration of breast cancer. Conclusions: The DUBRI discovered in this research may effectively evaluate the outlook of breast cancer patients and identify groups of patients who would gain advantages from immunotherapy, offering vital knowledge for the future targeted treatment of breast cancer patients.

Background Pathologically, clear cell renal cell carcinoma (ccRCC) is the most common type of renal carcinoma, with high heterogeneity and poor prognosis. There is increasing evidence that alternative splicing (AS) is involved in tumor evolution and tumor immune microenvironment (TIME). However, studies on the exploration of AS events and TIME in ccRCC are still few but needed. Methods The transcriptional data and clinicopathological information of patients with ccRCC in The Cancer Genome Atlas (TCGA) database were extracted completely. Patients were grouped according to the ESTIMATE algorithm and differentially expressed AS events (DEASs) were identified. The relationship between AS events and features of TIME were investigated by functional enrichment analysis and unsupervised consensus analysis. Finally, hub SF was identified by the regulatory network of survival-related AS events and intersection splicing factors (SFs), and its biological function was further verified in vitro. Results In total, the data of 515 patients with ccRCC were extracted and analyzed. Patients with low immune-score presented longer overall survival (OS) than high immune-score. 861 AS events were identified as DEASs, and they were enriched in immune-related pathways. 3 AS-based clusters were identified and found to have different prognoses and unique immune features. Finally, MBNL1 was identified as a hub SF, and it was shown to inhibit proliferation and metastasis, promote apoptosis, and block cells in G2/M phase in 786O and A498 cells. Conclusion The prognosticrisk model constructed base on immune-related AS events has good predictive ability for ccRCC, and the 3-clusters model based on immune-related AS events has potential for further clinical exploration. Thehub SF found in the present study, such as MBNL1, could affect the progression of ccRCC.

To systematically analyze the efficacy and toxicity of drugs targeting KRAS^G12C mutation in non-small cell lung cancer (NSCLC). The candidate studies were identified in PubMed, Embase, Cochrane Library, CNKI and Wanfang databases up to 1 June 2023. Data on efficacy, prognosis, and adverse events (AEs) were extracted and calculated by meta-analysis. Six eligible prospective studies were included in this meta-analysis, including 563 patients with advanced or metastatic NSCLC. For patients with NSCLC, the objective response rate (ORR) of drugs targeting KRAS^G12C mutation was 37% (95%CI 31-43), median duration of response (DOR) was 8.89 months (95%CI 7.96-9.83), and median progression-free survival (PFS) was 6.40 months (95%CI 5.86-6.93). The overall incidence of AEs was 88% (95%CI 79-96) and the incidence of grade ≥ 3 AEs was 44% (95%CI 24-64). The most common AEs were diarrhea, nausea, fatigue, and vomiting. The most common grade ≥ 3 AEs were Alaninetransaminase (ALT) or Aspartatetransaminase (AST) increased and diarrhea. Sotorasib, Adagrasib, and Garsorasib as the drugs of choice for patients with KRAS^G12C mutation NSCLC, have definite efficacy and acceptable safety, especially for patients with advanced or metastatic disease and within posterior line therapy.

This meta-analysis aims to systematically analyze the efficacy and toxicity of mirvetuximab soravtansine (MIRV) as second-line and above treatment for advanced or recurrent ovarian cancer. Candidate studies were identified in PubMed, Embase, Cochrane Library, CNKI, and Wanfang databases up to 1 May 2023. Objective response rate (ORR), progression-free survival (PFS), the incidence of adverse events (AEs), and incidence of grade ≥ 3 AEs were extracted and calculated by meta-analysis of merging ratios or mean to describe the efficacy and toxicity of MIRV. Seven eligible prospective studies were included in this meta-analysis, including 605 patients with advanced ovarian cancer who received second-line or higher therapy. ORR of MIRV was 34.2% (95% confidence interval [CI] 25.0-43.5), and PFS was 5.82 months (95%CI 4.47-7.18). The overall incidence of AEs was 87.4% (95%CI 52.9-100.0) and the incidence of grade ≥ 3 AEs was 27.1% (95%CI 18.9-36.1). The most common AEs were vision blurring, nausea, and diarrhea, with incidence of 46.7% (39.6-53.8), 41.8% (34.0-49.9), and 41.3% (30.4-52.5), respectively. MIRV has definite efficacy and good safety as a novel choice for second-line and above treatment of advanced or recurrent FRα positive ovarian cancer. This may have promising application in patients with platinum-resistant diseases. CRD42023428599.