CDK4/6 inhibitor abemaciclib combined with low-dose radiotherapy enhances the anti-tumor immune response to PD-1 blockade by inflaming the tumor microenvironment in Rb-deficient small cell lung cancer.

Background: Cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitors have shown significant activity against several solid tumors by reducing the phosphorylation of the canonical CDK4/6 substrate retinoblastoma (Rb) protein, while the anti-tumor effect of CDK4/6 inhibitors on Rb-deficient tumors is not clear. Most small cell lung cancers (SCLCs) are Rb-deficient and show very modest response to immune checkpoint blockade (ICB) despite recent advances in the use of immunotherapy. Here, we aimed to investigate the direct effect of CDK4/6 inhibition on SCLC cells and determine its efficacy in combination therapy for SCLC. Methods: The immediate impact of CDK4/6 inhibitor abemaciclib on cell cycle, cell viability and apoptosis in four SCLC cell lines was initially checked. To explore the effect of abemaciclib on double-strand DNA (ds-DNA) damage induction and the combination impact of abemaciclib coupled with radiotherapy (RT), western blot, immunofluorescence (IF) and quantitative real-time polymerase chain reaction (qRT-PCR) were performed. An Rb-deficient immunocompetent murine SCLC model was established to evaluate efficacy of abemaciclib in combination therapy. Histological staining, flow cytometry analysis and RNA sequencing were performed to analyze alteration of infiltrating immune cells in tumor microenvironment (TME). Results: Here, we demonstrated that abemaciclib induced increased ds-DNA damage in Rb-deficient SCLC cells. Combination of abemaciclib and RT induced more cytosolic ds-DNA, and activated the STING pathway synergistically. We further showed that combining low doses of abemaciclib with low-dose RT (LDRT) plus anti-programmed cell death protein-1 (anti-PD-1) antibody substantially potentiated CD8+ T cell infiltration and significantly inhibited tumor growth and prolonged survival in an Rb-deficient immunocompetent murine SCLC model. Conclusions: Our results define previously uncertain DNA damage-inducing properties of CDK4/6 inhibitor abemaciclib in Rb-deficient SCLCs, and demonstrate that low doses of abemaciclib combined with LDRT inflame the TME and enhance the efficacy of anti-PD-1 immunotherapy in SCLC model, which represents a potential novel therapeutic strategy for SCLC.

An online clinical model and risk stratification system to predict progression-free survival for advanced non-small-cell lung cancer patients treated with PD-(L)1 inhibitor.

Background: Our study aimed to build a risk stratification system predicting the progression-free survival (PFS) to classify patients into diverse prognostic subgroups for advanced non-small-cell lung cancer patients treated with PD-(L)1 inhibitor. Methods: 404 patients from our center were enrolled in this study and 70% patients (n = 282) were randomly assigned into the training cohort and other 30% patients (n = 122) into the validation cohort. A testing cohort contained 81 patients from other centers were used to assess the generalizability of model. Cox regression analyses were used to identify the most significant clinical parameters. The model's performance was assessed by using concordance index (C-index), calibration curves, Decision Curve Analyses (DCAs), net reclassification improvement (NRI), integrated discrimination improvement (IDI) analyses, and survival curve. Results: Five clinical parameters were identified as the most significant predictors by using cox regression. We then integrated them into a Nomogram to Evaluate the relative PFS of ICIs Treatment (NEPIT). The C-index of NEPIT in the training cohort, the validation cohort and testing cohort was 0.789 (95%CI: 0.750-0.828), 0.745 (95%CI: 0.706-0.784), and 0.766 (95%CI: 0.744-0.788), respectively. The calibration curves presented a good congruence between the predictions and actual observations. The Decision Curve Analyses (DCAs) reflected positive net benefits can be obtained for NEPIT. The results from NRI and IDI analyses showed that the NEPIT could improve predictive power of TPS. In addition, the further constructed risk stratification system could effectively categorize patients into different risk subgroups. Conclusion: The tools developed in this study would have value in guiding the optimal patient selection for precision care.

Larysuicide: an online risk stratification system to identify patients at high risk of suicide after the laryngeal cancer diagnosis.

BACKGROUND: Patients with laryngeal cancer have more than five times the incidence of suicide compared with the general population. In this study, we aimed to develop an online risk stratification system, named Larysuicide, to identify patients at high risk of suicide after the laryngeal cancer diagnosis. METHODS: Forty-two thousand and sixty-six American patients from the SEER-18 database and 4207 Chinese patients from our center were included in this study. We randomly assigned American patients into the training set and validation set at a ratio of 7:3, and all Chinese patients remained as an independent external testing set. LASSO regression model was applied for data dimension reduction, feature selection, and Larysuicide building. The performance of model was evaluated and validated by C-index, AUC, calibration curves, decision curve analysis (DCA), and univariate regression analysis. RESULTS: The Larysuicide developed with seven selected features-age, race, cancer site, pathological subtype, grade, stage at presentation, and radiation. The model showed good discrimination, with a C-index of 0.745 (95% CI 0.723-0.767) in training set, 0.759 (95% CI 0.722-0.800) in validation set, and 0.749 (95% CI 0.730-0.769) in testing set. The AUC was 0.745 in training set, 0.759 in validation set, and 0.749 in testing set. The calibration curves showed good calibration. Decision curve analysis demonstrated that Larysuicide was clinically useful. The univariate regression analysis presented patients in the high-risk group identified by Larysuicide suffered a significantly higher risk of committing suicide after cancer diagnosis. CONCLUSION: We constructed an online risk stratification system which could help health-care professionals efficiently identify patients at high risk of suicide after the laryngeal cancer diagnosis. Larysuicide could be a useful tool for health-care professionals to implement an early and appropriate psychological intervention in context of precision medicine.

Rapid response to monotherapy with MEK inhibitor trametinib for a lung adenocarcinoma patient harboring primary SDN1-BRAF fusion: A case report and literature review.

BRAF gene has been identified as an oncogenic driver and a potential target in various malignancies. BRAF fusions are one subtype of BRAF alterations with a rare frequency. Here, we first report a previously treated advanced lung adenocarcinoma patient with de novo SND1-BRAF fusion who achieves partial response to the MAK inhibitor trametinib. We also provide a literature review on targeted therapies for BRAF fusions.

Expression of Microtubule-Associated Proteins in Relation to Prognosis and Efficacy of Immunotherapy in Non-Small Cell Lung Cancer.

BACKGROUND: Microtubule-associated proteins (MAPs) have been considered to play significant roles in the tumor evolution of non-small cell lung cancer (NSCLC). Nevertheless, mRNA transcription levels and prognostic value of distinct MAPs in patients with NSCLC remain to be clarified. METHODS: In this study, the Oncomine database, Gene Expression Profiling Interactive Analysis (GEPIA) database, and Human Protein Atlas were utilized to analyze the relationship between mRNA/protein expression of different MAPs and clinical characteristics in NSCLC patients, including tumor type and pathological stage. The correlation between the transcription level of MAPs and overall survival (OS) of NSCLC patients was analyzed by Kaplan-Meier plotter. Besides, 50 frequently altered neighbor genes of the MAPs were screened out, and a network has been constructed via the cBioPortal and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) dataset. Meanwhile, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis on the expression data of MAPs and their 50 frequently altered neighbor genes in NSCLC tissues. Furthermore, The Cancer Immunome Atlas (TCIA) was utilized to analyze the relationship between MAP expression and the response to immunotherapy. Finally, we used reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to verify the expression of MAPs in 20 patients with NSCLC. RESULTS: The present study discovered that the mRNA transcription levels of MAP7/7D2 were enriched in NSCLC tissues, while those of the MAP2/4/6/7D3 were lower in NSCLC specimens than those in control specimens. The mRNA transcription level of MAP6 was significantly associated with the advanced stage of NSCLC. Besides, survival analysis indicated that higher mRNA expressions of MAP2/4/6/7/7D3 were correlated considerably with favorable OS of NSCLC patients, whereas increased mRNA expression levels of MAP1A/1S were associated with poor OS. Moreover, the expression of MAP1A/1B/1S/4/6/7D1/7D3 was significantly correlated with immunophenoscore (IPS) in NSCLC patients. CONCLUSIONS: Our analysis indicated that MAP1A/1S could serve as potential personalized therapeutic targets for patients with NSCLC, and the enriched MAP2/4/6/7/7D3 expression could serve as a biomarker for favorable prognosis in NSCLC. Besides, the expression of MAP1A/1B/1S/4/6/7D1/7D3 was closely related to the response to immunotherapy. Taken together, MAP expression has potential application value in the clinical treatment and prognosis assessment of NSCLC patients, and further verifiable experiments can be conducted to verify our results.

A risk classification system predicting the cancer-specific survival for postoperative stage IB non-small-cell lung cancer patients without lymphovascular and visceral pleural invasion.

BACKGROUND: This study aims to formulate a risk classification system predicting the cancer-specific survival (CSS) for postoperative stage IB NSCLC patients without lymphovascular (LVI) and visceral pleural (VPI) invasion to guide treatment decision making and assist patient counseling. METHOD: A total of 4,238 patients were included in this study. Patients were randomly divided into training and validation cohorts (7:3). The risk factors were identified by Cox regression. Concordance index (C-index), calibration curves, and Decision Curve Analyses (DCAs) were used to evaluate the performance of nomogram. We applied X-tile to calculate the optimal cut-off points and develop a risk classification system. The Kaplan-Meier method was conducted to evaluate CSS in different risk groups, and the significance was evaluated by log-rank test. RESULT: Among the 4,238 patients, 1,014(23.9%) suffered cancer-specific death. In the training cohort, univariable and multivariable Cox regression analyses revealed that age, gender, pathological subtype, grade, tumor size, the number of removed lymph nodes and surgical type were significantly associated with CSS. According to these results, the nomogram was formulated. The C-index of the prediction model was 0.755 in the training cohort (95%CI: 0.733-0.777) and 0.726 (95%CI: 0.695-0.757) in the validation cohort. The calibration curves in training and validation cohort exhibited good agreement between the predictions and actual observations. The Decision Curve Analyses (DCAs) showed net benefit can be achieved for nomogram. A risk classification system was further constructed that could perfectly classify patients into three risk groups. CONCLUSION: In this study, we constructed a nomogram to support individualized evaluation of CSS and a risk classification system to identify patients in the different risk groups in stage IB NSCLC patients without LVI and VPI. These tools could be useful in guiding treatment decision making and assisting patient counseling.

Overall Survival Analyses following Adjuvant Chemotherapy or Nonadjuvant Chemotherapy in Patients with Stage IB Non-Small-Cell Lung Cancer.

BACKGROUND: Adjuvant chemotherapy (ACT) can improve prognosis for stages II-IIIA patients with non-small-cell lung cancer (NSCLC), but its implication in stage I patients is still an intractable puzzle. This study aims to seek ACT candidates for stage IB NSCLC and establish a nomogram to predict overall survival (OS) of specific patient for clinician's decision. METHOD: We performed a retrospective study on 16,765 patients (ACT group: n = 2,187; non-ACT group: n = 14,578) from the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival was assessed in two groups. We performed propensity-score matching for risk adjustment. The risk factors were identified and used to create nomogram. Concordance index (C-index), Hosmer-Lemeshow test, and calibration were applied to evaluate model performance. To further evaluate the influence of tumor size on the selection of potential ACT candidates for patients with stage IB NSCLC, subgroup analyses were executed. RESULT: Survival analysis for the entire study cohort showed that ACT had better OS than non-ACT (HR = 0.800, CI: (0.751-0.851), P < 0.0001). In matched cohort, ACT also presented better OS than non-ACT (HR = 0.775, CI: (0.704-0.853), P < 0.0001). Univariate and multivariate Cox regression analysis revealed that eight prognostic factors, including gender, age, grade, pathological subtype, tumor size, visceral pleural invasion, surgical procedure, and the number of removed lymph nodes, were significantly correlated with OS. The nomogram was further constructed based on these prognostic factors. The C-index of nomogram was 0.639 (95%CI: 0.632-0.646). The Hosmer-Lemeshow test, and calibration presented good congruence between the predictions and actual observations. Subgroup analyses of tumor size group showed that ACT shared similar OS to non-ACT in NSCLC patients with tumor size ≤20 mm (P > 0.05). However, for NSCLC patients with 20 mm < size ≤30 mm (HR = 0.845, 95%CI (0.724-0.986), P=0.032) and 30 mm < size ≤40 mm (HR = 0.912, 95%CI (0.833-1.000), P=0.049), ACT associated with better OS. CONCLUSION: In this study, we found that ACT had better OS than non-ACT in patients with stage IB NSCLC. The nomogram provided an individual prediction of OS for patients after surgical resection. Patients with tumor size >20 mm and ≤40 mm may be potential candidates for ACT.

Prognostic significance of epigenetic regulatory gene expression in patients with non-small-cell lung cancer.

In this study, we used public databases to investigate the prognostic significance of epigenetic regulatory gene expression in patients with non small-cell lung cancer (NSCLC). Oncomine database analysis showed that the mRNA levels of seven epigenetic regulatory genes, UHRF1, EZH2, TTF2, SUV39H2, PCNA, WHSC1 and RAD54L, genes were significantly upregulated in NSCLC patients as compared to normal lung tissues. Functional enrichment analysis of these seven genes showed that the most enriched GO terms were DNA repair and rhythmic process, whereas, the most enriched KEGG pathway was lysine degradation pathway. The mRNA and protein expression levels of UHRF1, EZH2, TTF2, WHSC1 and RAD54L significantly correlated with tumor stage in NSCLC patients. Moreover, NSCLC patients exhibiting higher UHRF1, EZH2, WHSC1 and RAD54L mRNA and protein expression levels had poorer progression-free survival and overall survival. These findings demonstrate that UHRF1, EZH2, WHSC1 and RAD54L are potential prognostic biomarkers to distinguish high-risk from low-risk NSCLC patients.