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Abstract Small cell lung cancer (SCLC) is one of the highly aggressive malignancies characterized by rapid growth and early metastasis, but treatment options are limited. For SCLC, carboplatin or cisplatin in combination with etoposide chemotherapy has been considered the only standard of care, but the standard first‐line treatment only results in 10‐month survival. The majority of patients relapse within a few weeks to months after treatment, despite the relatively sensitive response to chemotherapy. Over the past decade, immunotherapy has made significant progress in the treatment of SCLC patients. However, there have been limited improvements in survival rates for SCLC patients with the current immune checkpoint inhibitors PD‐1/PD‐L1 and CTLA‐4. In the face of high recurrence rates, small beneficiary populations, and low survival benefits, the exploration of new targets for key molecules and signals in SCLC and the development of drugs with novel mechanisms may provide fresh hope for immunotherapy in SCLC. Therefore, the aim of this review was to explore four new targets, DLL3, TIGIT, LAG‐3, and GD2, which may play a role in the immunotherapy of SCLC to find useful clues and strategies to improve the outcome for SCLC patients.

Abstract Background The biomarkers of immune checkpoint inhibitors in the treatment of non‐small cell lung cancer (NSCLC) patients have limited predictive performance. In this study we aimed to investigate the feasibility of molecular tumor burden index (mTBI) in circulating tumor DNA (ctDNA) as a predictor for immunotherapy in patients with NSCLC. Methods From February 2017 to November 2020, pretreatment and on‐treatment (3~6 weeks after first cycle of immunotherapy) dynamic plasma ctDNA samples from NSCLC patients receiving immune monotherapy or combination therapy were analyzed by targeted capture sequencing of 1021 genes. PyClone was used to infer the mTBI. The impact of pretreatment mTBI on survival outcomes was verified in the POPLAR/OAK trials. Results We found that patients without detectable baseline ctDNA had better survival outcomes (median overall survival [OS]: not reached vs. 12.8 months; hazard ratio [HR], 0.15; p = 0.035]). RB1 and SMARCA4 mutations were remarkably associated with worse survival outcomes. Furthermore, lower pretreatment mTBI was associated with superior OS (median: not reached vs. 8.1 months; HR, 0.22; p = 0.024) and PFS (median: 32.9 vs. 5.4 months; HR, 0.35; p = 0.045), but not objective response, which was validated in the POPLAR/OAK cohort, suggesting that baseline mTBI was a prognostic factor for NSCLC immunotherapy. Early dynamic changes of mTBI (ΔmTBI) significantly distinguished responsive patients, and patients with mTBI decrease to more than 68% at the final tumor evaluation had longer OS (median: 38.2 vs. 4.0 months; HR, 0.18; p = 0.017) and PFS (median: not reached vs. 2.3 months; HR, 0.24; p = 0.030). Conclusion ΔmTBI had a good sensitivity to identify potential beneficial patients based on the best effect CT scans, demonstrating that mTBI dynamics were predictive of benefit from immune checkpoint blockade.

Summary: Comprehensive multiplatform analysis of Luminal B breast cancer (LBBC) specimens identifies two molecularly distinct, clinically relevant subtypes: Cluster A associated with cell cycle and metabolic signaling and Cluster B with predominant epithelial mesenchymal transition (EMT) and immune response pathways. Whole-exome sequencing identified significantly mutated genes including TP53, PIK3CA, ERBB2, and GATA3 with recurrent somatic mutations. Alterations in DNA methylation or transcriptomic regulation in genes (FN1, ESR1, CCND1, and YAP1) result in tumor microenvironment reprogramming. Integrated analysis revealed enriched biological pathways and unexplored druggable targets (cancer-testis antigens, metabolic enzymes, kinases, and transcription regulators). A systematic comparison between mRNA and protein displayed emerging expression patterns of key therapeutic targets (CD274, YAP1, AKT1, and CDH1). A potential ceRNA network was developed with a significantly different prognosis between the two subtypes. This integrated analysis reveals a complex molecular landscape of LBBC and provides the utility of targets and signaling pathways for precision medicine.

Abstract Purpose The mechanism of chemo‐resistance in small cell lung cancer (SCLC) is unclear. This study aims to explore the resistance‐related genomic profiles of residual tumors after neo‐adjuvant chemotherapy (NAC) in SCLC through the whole‐exome sequencing (WES). Experimental design A total of 416 limited diseases (LD) SCLC patients underwent surgery were retrospectively analyzed, of which 40 patients received NAC. Then we selected 29 patients undergoing NAC (n = 19) and chemotherapy naïve (CTN, n = 10) to perform WES sequence with formalin‐fixed paraffin‐embedded samples including tumor and paired para‐tumor. Results In total, single nucleotide variation and mutation rate were similar between NAC and CTN groups. The mutation signatures were significantly discrepant between NAC and CTN groups, as well as among patients with partial response (PR), stable disease (SD), and progressive disease. There were more copy number variation deletions in NAC group compared with CTN group. The inactivation of TP53 and RB1 were the most significantly events in both NAC and CTN groups. RB1 nonsense mutations were recurrent in NAC group (9/19 vs. 0/9, 47.4% vs. 0%) with favorable survival, while the frame‐shift deletions were frequent in CTN group (3/9 vs. 3/19, 33.3% vs.15.8%). Integrated function enrichment revealed that the frequently mutant genes were involved in cell cycle, metabolic reprogramming, and oncogenic signaling pathways in NAC group, such as BTG2 pathway, glycolysis in senescence and P53 pathway. A total of 27 genes presented frequently mutant in NAC group and might played a positive role in drug resistance. Multiple genes including BRINP3, MYH6, ST18, and PCHD15, which were associated with prognosis, occurred mutant frequently in PR and SD groups. Conclusion Residual tumors after neo‐adjuvant therapy exhibited different mutation signature spectrum. Multiple genes including RB1 nonsense mutations, BRINP3, MYH6, ST18, and PCHD15 were with frequent mutation in residual tumors, which might participate chemo‐resistance and influenced the prognosis in patients with limited disease SCLC.

Background and objective Immune checkpoint inhibitors (ICIs) improved survival of partial patients with lung squamous cell carcinoma (LUSC). However, it was still insufficient of data in older patients. This study aimed to investigate the efficacy and toxicity of immunotherapy in patients with LUSC in Chinese population of real world. Methods A total of 185 LUSC patients underwent pathological diagnosis were involved from January 2018 to January 2022. Patients were divided into elderly group (age ≥70 years) and younger group (age 0.05). The median progression-free survival (mPFS) and median overall survival (mOS) in elderly group were similar with younger group (P>0.05). Both combined group and immunology alone demonstrated prolonged mPFS in first-line compared with chemotherapy in elderly group. And combined group demonstrated significantly prolonged mPFS compared with chemotherapy in younger group (P0.05). Cox regression model demonstrated that clinical stage was an independent predictor and prognostic factor. The incidence of immune-related adverse was 58.0% (51/88) and grade 3 or above 25.0% (22/88). The most common grade 3 adverse events were rash, immune-associated pneumonia, and fatigue. Conclusion Immunology combined with chemotherapy increased ORR, mPFS and mOS of Chinese patients with LUSC in first-line therapy compared with chemotherapy. There was no difference of efficacy and adverse effects rate between elderly group and younger group. The adverse effects of immunology in elderly patients with LUSC were controllable.

Abstract Background The aim of this network meta‐analysis (NMA) was to evaluate the efficacy and safety of PD‐1/PD‐L1 inhibitors, alone or in combination with chemotherapy, as first‐line treatment for wild‐type advanced non‐small cell lung cancer. Methods We systematically searched databases, Clinical Trial.gov and included randomized clinical trials focusing on advanced NSCLC using PD‐1/PD‐L1 inhibitors as first‐line treatment. Hazard ratio for overall survival and progression‐free survival, odds ratio for any‐cause high‐adverse events (grade 3 or higher) were documented according to Bayesian NMA. Subgroup analysis was performed according to PD‐L1 level and histology. Results Thirteen trials including 9154 patients were included. In the PD‐L1 nonselective cohort, chemotherapy in combination with pembrolizumab and atezolizumab, respectively, were significantly better than any other treatment strategies in both OS benefit (HR = 0.63; HR = 0.85) and PFS benefit (HR = 0.52; HR = 0.63). In subgroup analysis, pembrolizumab appeared to provide the best OS benefit (HR = 0.67) as well as the best PFS benefit (HR = 0.67) in the PD‐L1 ≥ 50% cohort. In contrast, pembrolizumab combined with chemotherapy exhibited the best OS benefit in the PD‐L1

Abstract Background The aim of this study was to estimate the efficacy and safety of bevacizumab combined with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs) in advanced non‐small cell lung cancer (NSCLC) patients. Methods We searched randomized controlled trials (RCTs) on bevacizumab combined with EGFR TKIs in the NSCLC Cochrane Library, Web of Science, PubMed and Embase. The data were extracted and assessed according to the Cochrane Handbook. We calculated the hazard ratio (HR), risk ratio (RR), and confidence interval (CI), and accomplished this meta‐analysis with Stata 14 software. Results Of 1301 articles scanned, five articles were involved in this meta‐analysis. We determined that compared with using EGFR TKIs alone, combination treatment significantly prolongs progression‐free survival (PFS) (HR = 0.61, 95% CI = 0.52–0.70; p

This study was conducted to determine the correlation among serum biochemical indices, slaughter traits, texture characteristics and water-holding capacity in Tan sheep. Eighty Tan sheep aged 4–6 months were selected. Blood samples were collected from live animals to analyse serum biochemical indices. The slaughter traits, texture characteristics and water-holding capacity of meat were assessed after slaughter. There were highly significant correlations (p

Abstract Background Current predictive model is not developed by inflammation‐related genes to evaluate clinical outcome of breast cancer patients. Methods With mRNA expression profiling, we identified 3 mRNAs with significant expression between 15 normal samples and 669 breast cancer patients. Using 7 cell lines and 150 paraffin‐embedded specimens, we verified the expression pattern by bio‐experiments. Then, we constructed a three‐mRNA model by Cox regression method and approved its predictive accuracy in both training set (n = 1095) and 4 testing sets (n = 703). Results We developed a three‐mRNA (TBX21, TGIF2, and CYCS) model to stratify patients into high‐ and low‐risk subgroup with significantly different prognosis. In training set, 5‐year OS rate was 84.5% (78.8%‐90.5%) vs 73.1% (65.9%‐81.2%) for the low‐ and high‐risk group (HR = 1.573 (1.090‐2.271); P = 0.016). The predictive value was similar in four independent testing sets (HR>1.600; P

Abstract Background The Th1 cell-specific transcription factor TBX21 functions as a regulator of expression of a Th1 cytokine, interferon gamma (IFN-γ). However, the specific function of TBX21 correlated with cancer stemness remains unclear. Methods Using univariate and multivariate survival analysis, TBX21was identified as an independent predictive factor and was associated with poor prognosis in 1389 patients with lung adenocarcinoma (LUAD). Its mechanism in the prognosis was explored by functional enrichment analysis and validated in bioexperiments. Results In the training and test sets, TBX21 could classify 1389 LUAD patients into high and low-risk groups with significantly different prognosis (P < 0.01). Its prognostic power was independent of other clinical factors including stage, age, gender and smoking status. Functional studies indicated that downregulating TBX21 in lung cancer cells decreased the fraction of cancer stem cells and their sphere and tumor initiation frequency. Furthermore, the study showed that TBX21 activation transduced a TBX21–IL-4 signaling cascade to promote tumor initiation, tumor growth and expression of stemness markers. Conclusions These data demonstrated a key role of TBX21 in the maintenance of cancer stemness and that the TBX21–IL-4 pathway is a crucial factor contributing to lung carcinogenesis. Graphical abstract TBX21 prognostic model correlated with cancer stemness via TBX21-IL-4 pathway in LUAD patients

OBJECTIVES: MicroRNAs (miRNAs) play a key role in governing posttranscriptional regulation through binding to the mRNAs of target genes. This study is to assess miRNAs expression profiles for identifying brain metastasis-related miRNAs to develop the predictive model by microarray in tumor tissues. METHODS: For this study, we screened the significant brain metastasis-related miRNAs from 77 lung adenocarcinoma (LUAD) patients with brain metastasis (BM+) or non-brain metastasis (BM−). A predictive model was developed from the training set (n = 42) using a random Forest supervised classification algorithm and a Class Centered Method, and then validated in a test set (n = 35) and further analysis in GSE62182 (n = 73). The independence of this signature in BM prediction was measured by multivariate logistic regression analysis. RESULTS: From the training set, the predictive model (including hsa-miR-210, hsa-miR-214 and hsa-miR-15a) stratified the patients into two groups with significantly different BM subtypes (90.4% of accuracy). The similar predictive power (91.4% of accuracy) was obtained in the test cohort. As an independent predictive factor, it was closely associated with BM and had high sensitivity and specificity in predicting BM in clinical practice. Moreover, functional enrichment analysis demonstrated that this signature involved in the signaling pathways positively correlated with cancer metastasis. CONCLUSION: These results suggested that the three-miRNA signature could develop a new random Forest model to predict the BM of LUAD patients. These findings emphasized the importance of miRNAs in diagnosing BM, and provided evidence for selecting treatment decisions and designing clinical trials.

We present a self-contained theory for the exact calculation of particle number counting statistics of noninteracting indistinguishable particles in the canonical ensemble. This general framework introduces the concept of auxiliary partition functions, and represents a unification of previous distinct approaches with many known results appearing as direct consequences of the developed mathematical structure. In addition, we introduce a general decomposition of the correlations between occupation numbers in terms of the occupation numbers of individual energy levels, that is valid for both nondegenerate and degenerate spectra. To demonstrate the applicability of the theory in the presence of degeneracy, we compute energy-level correlations up to fourth order in a bosonic ring in the presence of a magnetic field.