Characteristics and prognosis of EGFR mutations in small cell lung cancer patients in the NGS era.

PURPOSE: Targeted therapy has not been effective for small cell lung cancer (SCLC) patients. Although some studies have reported on EGFR mutations in SCLC, a systematic investigation into the clinical, immunohistochemical, and molecular characteristics and prognosis of EGFR-mutated SCLCs is lacking. METHODS: Fifty-seven SCLC patients underwent next-generation sequencing technology, with 11 in having EGFR mutations (group A) and 46 without (group B). Immunohistochemistry markers were assessed, and the clinical features and first-line treatment outcomes of both groups were analyzed. RESULTS: Group A consisted primarily of non-smokers (63.6%), females (54.5%), and peripheral-type tumors (54.5%), while group B mainly comprised heavy smokers (71.7%), males (84.8%), and central-type tumors (67.4%). Both groups showed similar immunohistochemistry results and had RB1 and TP53 mutations. When treated with tyrosine kinase inhibitors (TKIs) plus chemotherapy, group A had a higher treatment response rate with overall response and disease control rates of 80% and 100%, respectively, compared to 57.1% and 100% in group B. Group A also had a significantly longer median progression-free survival (8.20 months, 95% CI 6.91-9.49 months) than group B (2.97 months, 95% CI 2.79-3.15), with a significant difference (P = 0.043). Additionally, the median overall survival was significantly longer in group A (16.70 months, 95% CI 1.20-32.21) than in group B (7.37 months, 95% CI 3.85-10.89) (P = 0.016). CONCLUSION: EGFR-mutated SCLCs occurred more frequently in non-smoking females and were linked to prolonged survival, implying a positive prognostic impact. These SCLCs shared immunohistochemical similarities with conventional SCLCs, and both types had prevalent RB1 and TP53 mutations.

Assessing the Optimal Regimen: A Systematic Review and Network Meta-Analysis of the Efficacy and Safety of Long-Acting Granulocyte Colony-Stimulating Factors in Patients with Breast Cancer.

Patients with breast cancer undergoing chemotherapy are susceptible to prolonged and severe neutropenia. Multiple biosimilars of long-acting granulocyte colony-stimulating factors (LA-G-CSFs) have been newly developed to prevent this disease. Nonetheless, which LA-G-CSF regimen has the optimal balance of efficacy and safety remains controversial. Moreover, there is a lack of evidence supporting clinical decisions on LA-G-CSF dose escalation in poor conditions. PubMed, Embase, Cochrane Library, Web of Science, and several Chinese databases were searched (December 2022) to collect randomized controlled trials (RCTs) about LA-G-CSFs preventing chemotherapy-induced neutropenia in breast cancer patients. No restrictions were imposed on language. A Bayesian network meta-analysis was performed. We assessed the incidence of severe neutropenia (SN) and febrile neutropenia (FN), the duration of SN (DSN), and the absolute neutrophil account recovery time (ANCrt) for efficacy, while the incidence of severe adverse events (SAE) was assessed for safety. The study was registered in PROSPERO (CRD42022361606). A total of 33 RCTs were included. Our network meta-analysis demonstrated that lipegfilgrastim 6 mg and eflapegrastim 13.2 mg outperformed other LA-G-CSFs with high efficacy rates and few safety concerns (SUCRA of lipegfilgrastim 6 mg: ANC rt 95.2%, FN 97.4%; eflapegrastim 13.2 mg: FN 87%, SN 89.3%). Additionally, 3.6 mg, 4.5 mg, 6 mg, and 13.2 mg dosages all performed significantly better than 1.8 mg in reducing the duration of SN (3.6 mg: DSN, SMD -0.68 [-1.13, -0.22; moderate]; 4.5 mg: -0.87 [-1.57, -0.17; low]; 6 mg: -0.89 [-1.49, -0.29; moderate]; 13.2 mg: -1.02 [1.63, -0.41; high]). Increasing the dosage from the guideline-recommended 6 mg to 13.2 mg can reduce both the duration and incidence of SN (SMD -0.13 [-0.24 to -0.03], RR 0.65 [0.43 to 0.96], respectively), with no significant difference in SAE. For patients with breast cancer, lipegfilgrastim 6 mg and eflapegrastim 13.2 mg might be the most effective regimen among LA-G-CSFs. Higher doses of LA-G-CSF may enhance efficacy without causing additional SAEs.

Machine learning-based construction of a ferroptosis and necroptosis associated lncRNA signature for predicting prognosis and immunotherapy response in hepatocellular cancer.

Introduction: Liver hepatocellular carcinoma (LIHC), one of the most common malignancies worldwide, occurs with high incidence and mortality. Ferroptosis and necroptosis are critically associated with LIHC prognosis. Some long non-coding RNAs (lncRNAs) have been found to induce ferroptosis and necroptosis in hepatocellular carcinoma cells. Methods: Cox regression analysis was used to construct a risk model for LIHC based on differentially expressed ferroptosis and necroptosis related lncRNAs (F-NLRs), and their expression in SMMC7721, HepG2 and WRL68 cells was detected by qPCR. Results: Five F-NLRs were associated with LIHC prognosis, including KDM4A-AS1, ZFPM2-AS1, AC099850.3, MKLN1-AS, and BACE1-AS. Kaplan-Meier survival analysis indicated that patients with LIHC in the high-risk group were associated with poor prognosis. The combined F-NLR signature model demonstrated a prognostic AUC value of 0.789 and was more accurate than standard clinical variables for predicting LIHC prognosis. T cell functions and immunotherapy responses differed significantly between patients in the low- and high-risk groups. Additionally, immune checkpoints and m6A-related genes were differentially expressed between patients in the two risk groups. Furthermore, proteins encoded by the five F-NLRs were overexpressed in four liver cancer cell lines compared to that in human liver cell line WRL68. Pan-cancer examination revealed that expression levels of the five F-NLRs differed between most common tumor types and normal tissues. Conclusion: F-NLRs identified in this study provide a predictive signature representing ferroptosis and necroptosis in LIHC, which correlated well with patient prognosis, clinicopathological characteristics, and immunotherapy responses. The study findings help to elucidate the mechanisms of F-NLRs in LIHC and provide further guidance for the selection and development of immunotherapeutic agents for LIHC.

Accuracy of minimal residual disease detection by circulating tumor DNA profiling in lung cancer: a meta-analysis.

BACKGROUND: The sensitivity and specificity of minimal residual disease detected by circulating tumor DNA profiling (ctDNA MRD) in lung cancer, with particular attention to the distinction between landmark strategy and surveillance strategy, for predicting relapse in lung cancer patients after definitive therapy has yet to be determined. METHODS: The prognostic value of ctDNA MRD by landmark strategy and surveillance strategy was evaluated in a large cohort of patients with lung cancer who received definitive therapy using a systemic literature review and meta-analysis. Recurrence status stratified by ctDNA MRD result (positive or negative) was extracted as the clinical endpoint. We calculated the area under the summary receiver operating characteristic curves, and pooled sensitivities and specificities. Subgroup analyses were conducted based on histological type and stage of lung cancer, types of definitive therapy, and ctDNA MRD detection methods (detection technology and strategy such as tumor-informed or tumor-agnostic). RESULTS: This systematic review and meta-analysis of 16 unique studies includes 1251 patients with lung cancer treated with definitive therapy. The specificity of ctDNA MRD in predicting recurrence is high (0.86-0.95) with moderate sensitivity (0.41-0.76), whether shortly after treatment or during the surveillance. The landmark strategy appears to be more specific but less sensitive than the surveillance strategy. CONCLUSIONS: Our study suggests that ctDNA MRD is a relatively promising biomarker for relapse prediction among lung cancer patients after definitive therapy, with a high specificity but suboptimal sensitivity, whether in landmark strategy or surveillance strategy. Although surveillance ctDNA MRD analysis decreases specificity compared with the landmark strategy, the decrease is minimal compared to the increase in sensitivity for relapse prediction of lung cancer.

Gefitinib Plus Chemotherapy vs Gefitinib Alone in Untreated EGFR-Mutant Non-Small Cell Lung Cancer in Patients With Brain Metastases: The GAP BRAIN Open-Label, Randomized, Multicenter, Phase 3 Study.

Importance: Use of tyrosine kinase inhibitors (TKIs) is the standard therapy for epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) with brain metastases. Several studies have shown that adding chemotherapy to EGFR-TKIs could improve progression-free survival (PFS) in patients with EGFR-mutant advanced NSCLC; however, the efficacy of these agents in patients with brain metastases remains unclear. Objective: To investigate the efficacy and safety of gefitinib plus chemotherapy (pemetrexed with platinum) compared with gefitinib alone in patients with untreated EGFR-mutant NSCLC brain metastases. Design, Setting, and Participants: This open-label prospective, multicenter, phase 3 randomized clinical trial was conducted in 6 centers in China from January 13, 2016, to August 27, 2021. The median follow-up time was 21.1 months (IQR, 13.5-31.8 months). Patients with untreated confirmed brain metastases and EGFR-sensitive mutated NSCLC were enrolled. Interventions: The eligible patients were randomly assigned (1:1) to receive gefitinib plus chemotherapy or gefitinib alone. Main Outcomes and Measures: The primary end point was intracranial PFS; secondary end points included PFS, overall survival (OS), intracranial objective response rate, overall objective response rate, and safety. Intention-to-treat analysis was performed. Results: A total of 161 patients (87 [54.0%] women; mean [SD] age, 55 [9.8] years; range, 26-80 years) were enrolled and randomized to receive gefitinib (n = 81) or gefitinib plus chemotherapy (n = 80). The median intracranial PFS was 15.6 months (95% CI, 14.3-16.9 months) in the gefitinib plus chemotherapy group vs 9.1 months (95% CI, 8.0-10.2 months) in the gefitinib group (hazard ratio, 0.36; 95% CI, 0.25-0.53; P < .001). Similarly, the median PFS was significantly longer with gefitinib plus chemotherapy than gefitinib alone (16.3; 95% CI, 14.4-18.2 months vs 9.5; 95% CI, 8.3-10.8 months; P < .001). Gefitinib plus chemotherapy had a better intracranial objective response rate (85.0%; 95% CI, 77.0%-93.0% vs 63.0%; 95% CI, 52.2%-73.7%; P = .002) and overall objective response rate (80.0%; 95% CI, 71.0%-89.0% vs 64.2%; 95% CI, 53.5%-74.9%; P = .03) than gefitinib alone. At data cutoff, the median OS was also significantly longer in the gefitinib plus chemotherapy group vs the gefitinib group (35.0 vs 28.9 months; hazard ratio, 0.65; 95% CI, 0.43-0.99; P = .04). Grade 3 or worse adverse events were more common with gefitinib plus chemotherapy, most of which were manageable. Conclusions and Relevance: In this randomized clinical trial, gefitinib plus chemotherapy significantly improved intracranial PFS, PFS, and OS compared with gefitinib alone in patients with untreated EGFR-mutant NSCLC brain metastases and could be an optional first-line treatment for these patients. Trial Registration: ClinicalTrials.gov Identifier: NCT01951469.

Homologous recombination repair gene mutations as a predictive biomarker for immunotherapy in patients with advanced melanoma.

Background: Nowadays, immunotherapy targeting immune checkpoint receptors is one of the cornerstones of systemic treatment in melanoma. Homologous recombination repair (HRR) is one of the DNA damage response (DDR) pathways, which has been proved to correlate with the efficacy of platinum-based chemotherapy, PARP inhibitor therapy, and immunotherapy in a variety of cancers. However, their predictive value of HRR remained unknown in patients with advanced melanoma. Methods: Data of advanced melanoma patients from an independent cohort (Samstein2018) were used to analyze the correlation with immunogenic markers and the prognostic effect of HRR on immunotherapy, and another four cohorts (pooled cohort: Miao2018, Allen 2015, Hugo2016, and Synder2014) were used for validation. Immune infiltration cell scores analyzed by TCGA-SKCM cohort were used to explore potential mechanisms related to the immune microenvironment. Results: Compared to patients with an HRR wild type (HRRwt), those with HRR mutations (HRRmut) in anti-CTLA-4-treated patients of the Samstein2018 cohort had higher tumor mutation burden (TMB; P = 0.0041) and longer median overall survival (mOS; P = 0.0094). In terms of results validation, it was also confirmed that the mOS (P = 0.0014) of HRRmut patients receiving anti-CTLA-4 therapy was significantly better than that of HRRwt patients in the pooled cohort, and objective response rates (ORR; P = 0.0053) were also found to be significant. However, there was no significant difference in mOS between HRRmut patients who received anti-PD-1/L1 therapy and HRRwt patients in either the discovery (Samstein2018 cohort, P = 0.94) or validation (pooled cohort, P = 0.96) set. Exploratory analysis found that although HRRmut patients showed no significant difference in mOS between anti-CTLA-4 and anti-PD-1/L1 therapy (P = 0.79), the mOS value of the anti-CTLA-4 therapy group (31.7 months) in HRRmut patients was numerically superior to the anti-PD-1/L1 therapy group (27.5 months). In contrast, the mOS of the anti-CTLA-4 therapy group was significantly lower than that of the anti-PD-1/L1 therapy group (12.4 vs. 32.0 months) in HRRwt patients. In addition, transcriptome profiling analysis revealed that the 29 (65.9%)-gene mutation of the HRR pathway associated with reshaping of the immunological microenvironment in melanoma. Conclusions: HRR mutations were associated with a higher TMB level, and better anti-CTLA-4 therapy outcomes. HRR may serve as an independent predictor of anti-CTLA-4 therapy efficacy in patients with advanced melanoma and their clinical value warrants further investigation.

The Airway Microbiota Signatures of Infection and Rejection in Lung Transplant Recipients.

Infection and rejection are the two most common complications after lung transplantation (LT) and are associated with increased morbidity and mortality. We aimed to examine the association between the airway microbiota and infection and rejection in lung transplant recipients (LTRs). Here, we collected 181 sputum samples (event-free, n = 47; infection, n = 103; rejection, n = 31) from 59 LTRs, and performed 16S rRNA gene sequencing to analyze the airway microbiota. A significantly different airway microbiota was observed among event-free, infection and rejection recipients, including microbial diversity and community composition. Nineteen differential taxa were identified by linear discriminant analysis (LDA) effect size (LEfSe), with 6 bacterial genera, Actinomyces, Rothia, Abiotrophia, Neisseria, Prevotella, and Leptotrichia enriched in LTRs with rejection. Random forest analyses indicated that the combination of the 6 genera and procalcitonin (PCT) and T-lymphocyte levels showed area under the curve (AUC) values of 0.898, 0.919 and 0.895 to differentiate between event-free and infection recipients, event-free and rejection recipients, and infection and rejection recipients, respectively. In conclusion, our study compared the airway microbiota between LTRs with infection and acute rejection. The airway microbiota, especially combined with PCT and T-lymphocyte levels, showed satisfactory predictive efficiency in discriminating among clinically stable recipients and those with infection and acute rejection, suggesting that the airway microbiota can be a potential indicator to differentiate between infection and acute rejection after LT. IMPORTANCE Survival after LT is limited compared with other solid organ transplantations mainly due to infection- and rejection-related complications. Differentiating infection from rejection is one of the most important challenges to face after LT. Recently, the airway microbiota has been reported to be associated with either infection or rejection of LTRs. However, fewer studies have investigated the relationship between airway microbiota together with infection and rejection of LTRs. Here, we conducted an airway microbial study of LTRs and analyzed the airway microbiota together with infection, acute rejection, and clinically stable recipients. We found different airway microbiota between infection and acute rejection and identify several genera associated with each outcome and constructed a model that incorporates airway microbiota and clinical parameters to predict outcome. This study highlighted that the airway microbiota was a potential indicator to differentiate between infection and acute rejection after LT.

Cancer risks in rheumatoid arthritis patients who received immunosuppressive therapies: Will immunosuppressants work?

Background: Exploring the cancer risks of rheumatoid arthritis (RA) patients with disease-modifying anti-rheumatic drugs (DMARDs) can help detect, evaluate, and treat malignancies at an early stage for these patients. Thus, a comprehensive analysis was conducted to determine the cancer risk of RA patients using different types of DMARDs and analyze their relationship with tumor mutational burdens (TMBs) reflecting immunogenicity. Methods: A thorough search of PubMed, EMBASE, Web of Science, and Medline was conducted up to 20 August 2022. Standardized incidence ratios (SIRs) were constructed with a random-effect model to determine risks for different types of malignancies in comparison with the general population. We also analyzed the correlation between SIRs and TMBs using linear regression (LR). Results: From a total of 22 studies, data on 371,311 RA patients receiving different types of DMARDs, 36 kinds of malignancies, and four regions were available. Overall cancer risks were 1.15 (SIR 1.15; 1.09-1.22; p < 0.001) and 0.91 (SIR 0.91; 0.72-1.14; p = 0.402) in RA populations using conventional synthetic DMARDs (csDMARDs) and biologic DMARDs (bDMARDs), respectively. RA patients taking csDMARDs displayed a 1.77-fold lung cancer risk (SIR 1.77; 1.50-2.09; p < 0.001), a 2.15-fold lymphoma risk (SIR 2.15; 1.78-2.59; p < 0.001), and a 1.72-fold melanoma risk (SIR 1.72; 1.26-2.36; p = 0.001). Correlation coefficients between TMBs and SIRs were 0.22 and 0.29 from those taking csDMARDs and bDMARDs, respectively. Conclusion: We demonstrated a cancer risk spectrum of RA populations using DMARDs. Additionally, TMBs were not associated with elevated cancer risks in RA patients following immunosuppressive therapy, which confirmed that iatrogenic immunosuppression might not increase cancer risks in patients with RA. Interpretation: Changes were similar in cancer risk after different immunosuppressive treatments, and there was a lack of correlation between SIRs and TMBs. These suggest that we should look for causes of increased risks from the RA disease itself, rather than using different types of DMARDs.

Application of artificial intelligence in COVID-19 medical area: a systematic review.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a large-scale global epidemic, impacting international politics and the economy. At present, there is no particularly effective medicine and treatment plan. Therefore, it is urgent and significant to find new technologies to diagnose early, isolate early, and treat early. Multimodal data drove artificial intelligence (AI) can potentially be the option. During the COVID-19 Pandemic, AI provided cutting-edge applications in disease, medicine, treatment, and target recognition. This paper reviewed the literature on the intersection of AI and medicine to analyze and compare different AI model applications in the COVID-19 Pandemic, evaluate their effectiveness, show their advantages and differences, and introduce the main models and their characteristics. METHODS: We searched PubMed, arXiv, medRxiv, and Google Scholar through February 2020 to identify studies on AI applications in the medical areas for the COVID-19 Pandemic. RESULTS: We summarize the main AI applications in six areas: (I) epidemiology, (II) diagnosis, (III) progression, (IV) treatment, (V) psychological health impact, and (VI) data security. The ongoing development in AI has significantly improved prediction, contact tracing, screening, diagnosis, treatment, medication, and vaccine development for the COVID-19 Pandemic and reducing human intervention in medical practice. DISCUSSION: This paper provides strong advice for using AI-based auxiliary tools for related applications of human diseases. We also discuss the clinicians' role in the further development of AI. They and AI researchers can integrate AI technology with current clinical processes and information systems into applications. In the future, AI personnel and medical workers will further cooperate closely.

Skin microbiome differences relate to the grade of acne vulgaris.

The skin microbiome plays important roles in the pathogenesis and development of acne. We aimed to investigate the facial skin microbiome of acne and microbiome differences related to different grades of acne. Skin swabs from nine healthy controls and 67 acne patients were collected, and the skin microbiomes were analyzed using 16S rRNA gene sequencing. Compared with healthy controls, acne patients harbored significantly altered skin microbiomes. The skin microbiomes of patients with grade 1-3 acne were similar, but patients with grade 4 acne showed a significantly different skin microbiome compared with grade 1-3 acne, including increased alpha diversity and increased proportions of four Gram-negative bacteria (Faecalibacterium, Klebsiella, Odoribacter and Bacteroides). In conclusion, acne patients harbored an altered skin microbiome, and more significant dysbiosis was found in patients with grade 4 acne (severe acne). Our findings may provide evidence for the pathogenic mechanisms of acne and microbial-based strategies to avoid and treat acne, especially grade 4 acne.

T cell receptor repertoire profiling predicts the prognosis of HBV-associated hepatocellular carcinoma.

Tumor-infiltrating T cell repertoire has been demonstrated to be closely associated with anti-tumor immune response. However, the relationship between T cell repertoire in tumor tissue and prognosis has never been reported in Hepatocellular carcinoma (HCC). We performed the high-throughput T cell receptor (TCR) sequencing to systematically characterize the infiltrating T cell repertoires of tumor and matched adjacent normal tissues from 23 HBV-associated HCC patients. Significant differences on usage frequencies of some Vß, Jß, and Vß-Jß paired genes have been found between the 2 groups of tissue samples, but no significant difference of TCR repertoire diversity could be found. Interestingly, the similarity of TCR repertoires between paired samples or the TNM stage alone could not be helpful to evaluate the prognosis of patients very well, but their combination could serve as an efficient prognostic indicator that the patients with early stage and high similarity showed a better prognosis. This is the first attempt to assess the potential value of TCR repertoire in HCC prognosis, and our findings could serve as a complement for the characterization of TCR repertoire in HCC.