bluuebunny/crossref_metadata_2025_split huggingface dataset:
The clinical implications of TMB and the relationship between TMB and EGFR mutations in non-small cell lung cancer of Xuanwei, China.
Authors: Peng Hao , Zhang Hushan , Zhang Libin , Xu Zheyuan , Wang Yang , Wang Han 
Published: June 2022

e20512 Background: Xuanwei lung cancer is a type of non-small cell lung cancer that occurs in Xuanwei, southwest China. It is different from non-Xuanwei non-small cell lung cancer in many aspects. The key is that Xuanwei lung cancer does not currently have a recognized prognostic biomarker. The significant molecular difference between Xuanwei lung cancer and non-Xuanwei lung cancer is the mutation type and mutation ratio of EGFR. Are different mutations of EGFR related to the prognosis of Xuanwei lung cancer? What are the reasons for the difference between Xuanwei lung cancer and non-Xuanwei lung cancer? These are clinical issues that we are very interested in. In addition, tumor mutation burden (TMB) has been shown to be an effective biomarker for predicting the clinical outcome of multiple cancer types. However, its prognostic value in Xuanwei lung cancer remains unknown. Methods: The Formalin-Fixed Paraffin-Embedded (FFPE) tissues samples from 172 primary NSCLC patients who have underwent next-generation sequencing (NGS) in a laboratory accredited by the College of American Pathologists (CAP) and Clinical Laboratory Improvement Amendment (CLIA) (3D Medicines Inc., Shanghai, China) from June 2015 to October 2020 were analyzed. The written informed consent was obtained from all included patients. The postoperative follow-up data of all these NSCLC patients were collected. Results: The prognosis of Xuanwei lung cancer is better than that of non-Xuanwei (p < 0.05). Xuanwei is superior to non-Xuanwei mainly in EGFR-positive patients (p < 0.05). Among patients without EGFR mutations, there is no difference in the prognosis of Xuanwei lung cancer and non-Xuanwei lung cancer. Further analysis revealed that there is a difference in TMB levels between Xuanwei lung cancer and non-Xuanwei lung cancer. The TMB level in Xuanwei lung cancer is significantly higher than that in non-Xuanwei lung cancer (p < 0.05). EGFR mutations can be used as prognostic markers for Xuanwei lung cancer, and this is related to patients with EGFR mutations having higher TMB levels. Our research results indicate that EGFR mutation may help combine traditional clinicopathological risk factors to optimize risk stratification and guide treatment decisions. Conclusions: Xuanwei lung cancer is a special subtype of NSCLC with different molecular features and prognosis. Analysis of data in this area will lead to the development of precision treatment options for Xuanwei lung cancer.
EGFR mutations in lung carcinomas: Mutation profile and survival analysis.
Authors: Warrier Narayanankutty Edavalath , Vallathol Dilip Harindran , Sankar Uma V , Salahuddin Sameer , P. S. Sreedharan , Parameswaran Prasanth V. , K V Sajeevan 
Published: June 2022

e20518 Background: Epidermal growth factor receptor (EGFR) mutation have been demonstrated to be both predictive and prognostic for patients with metastatic lung cancer. The administration of EGFR tyrosine kinase inhibitors (TKIs) has improved survival in this group of patients. Several generations of EGFR TKIs are currently available. The EGFR mutations have been divided into common and rare. The common mutations include Exon 19 deletion and Exon 21 L858R mutations and rest are grouped as rare. The presence of visceral metastasis in the brain and liver are usually portends a poor prognosis. Methods: We conducted a retrospective analysis of lung cancer patients who attended our hospital outpatient department from 2017 to 2021. The prevalence, demographics and clinical profile of EGFR common and rare mutations were studied using descriptive statistics. Survival of EGFR mutated patients was plotted using Kaplan Meier plots. SPSS was used for statistical analysis. Results: The prevalence of EGFR mutation among metastatic lung cancer was 14.10% (161/1148). The median age of the group was 60 years (23- 104 years). Smokers with EGFR mutations were 11.8% (n = 19). Male to Female ratios was 76:85 (47.2% and 52.8%). Three patients with squamous cell carcinoma exhibited EGFR mutation. Most common EGFR TKI used was Gefitnib. Osimertinib was used in 13 patients (1.4%). The percentage of common mutations were 85.75% (N = 132) and rare mutations were 14.3% (n = 22). The type of mutations could not be identified in 10 patients. The percentage of patients with exon 19 deletion were 63% (n = 97) and L858R were 24.7% (n = 38). Visceral metastasis (brain and liver) was seen in 47 patients (n = 29.2%). Brain progression was seen in 32 patients (n = 19.9%). The survival of patients with EGFR exon 19 deletion and L858R mutation was 16.36 + 8.97 months and 15.97+ 10.93 months, Survival among patients with common mutation was 16.20 + 9.57 months and among rare mutation was 13.43 + 12.19 months. Median Survival period of patients with visceral metastasis was 12 months (0 to 38 months). Conclusions: In our retrospective study, there was no significant difference between survival among common and rare EGFR mutations.
Discordant genomic correlates of PD-L1 expression in lung adenocarcinoma among multiple cohorts using dissimilar PD-L1 testing techniques.
Authors: Wang Lijie , Liu Siyao 
Published: June 2022

e20526 Background: Programmed death-ligand 1 (PD-L1) is a crucial biomarker predicting efficacious treatment of immune checkpoint inhibitors (ICIs). Previous studies identified distinct staining utility among multiple PD-L1 antibodies, however, whether the genomic correlate of stained PD-L1 is also impacted by different testing assays is largely unknown. Methods: Here, we analyzed 873 lung adenocarcinoma (LUAD) samples by the FDA-approved SP263 and 22C3 antibodies, and discovered that TP53, KRAS, MET, and ALK alterations associated with high SP263/22C3-PD-L1 expression, while EGFR and ERBB2 aberrations linked to SP263/22C3-PD-L1 negativity. Results: We retrieved the data of 873 LUAD patients whose PD-L1 (SP263/22C3) and mutational data. The SP263/22C3-PD-L1 expression was significantly correlated with tumor mutational burden and was greater in metastatic lymph node than lung lesion and distal metastasis. Furthermore, TP53, MET, ALK, KRAS alterations were associated with higher SP263/22C3-PD-L1 expression, while EGFR and ERBB2 alterations were linked to SP263/22C3-PD-L1 negativity. In the TCGA database lacking fusion data except for ALK and using reverse phase protein arrays (RPPA) for quantifying PD-L1 expression, STK11 mutation exhibited negative correlation with PD-L1 mRNA (p < 0.001), but not the RPPA-PD-L1 protein-level expression (p > 0.10), while samples with ALK fusion showed a tendency of higher RPPA-PD-L1 (p = 0.088). Moreover, in the OAK trial providing data of single nucleotide variation and using SP142 (Ventana, Tucson, AZ) assay evaluating both tumor and immune cells, weak correlation between STK11 mutation and SP142-PD-L1 negativity was observed (p = 0.076). Conclusions: Identical usage of staining antibody is the fundament of further comparisons and deeper investigations. The FDA-approved SP263 and 22C3 assays with fixed reagent, machine and protocol may perform more effective and repeatable than LDTs such as the E1L3N method. In addition to the different staining utility among PD-L1 antibodies indicated by previous studies, we further provide insights into the dissimilar genomic correlates of stained PD-L1 by using different PD-L1 quantifying techniques.
Predicting patient treatment response and resistance via single-cell transcriptomics of their tumors.
Authors: SInha Sanju , Vegesna Rahulsimham , Dhruba Saugato Rahman , Wu Wei , Kerr D. Lucas , Stroganov Oleg V. , Grishagin Ivan , Aldape Kenneth D. , Blakely Collin M. , Jiang Peng , Thomas Craig J , Bivona Trever G. , Schaffer Alejandro , Ruppin Eytan 
Published: June 2022

e20540 Background: Tailoring the best treatments to cancer patients is an important open challenge. Here, we build a precision oncology data science and software framework for PERsonalized single-Cell Expression-based Planning for Treatments In Oncology (PERCEPTION). Methods: Our approach capitalizes on recently published matched bulk and single-cell transcriptome profiles of large-scale cell-line drug screens to build treatment response models from patients’ single-cell (SC) tumor transcriptomics. Our approach is a two-step process: first, the prediction models are trained on large-scale bulk-expression profiles of cancer cell lines and then, in a second step, the models’ performance is further optimized by training on SC-expression profiles of cancer cell lines. Results: First, we show that PERCEPTION successfully predicts the response to monotherapy and combination treatments in screens performed in cancer and patient-tumor-derived primary cells based on SC-expression profiles. Second, it successfully stratifies responders to combination therapy based on the patients’ tumor’s SC-expression in two very recent multiple myeloma and breast cancer clinical trials. Thirdly, it captures the development of clinical resistance to five standard tyrosine kinase inhibitors using tumor SC-expression profiles obtained during treatment in a lung cancer patients’ cohort. Notably, PERCEPTION outperforms state-of-the-art bulk expression-based predictors in all three clinical cohorts. Conclusions: In sum, this study provides a first-of-its-kind conceptual and computational method that is predictive of response to therapy in patients, based on the clonal SC gene expression of their tumors.
Blockade of STAT3/IL-4 overcomes EGFR T790M-cis-L792F-induced resistance to osimertinib via promoting M2 macrophages polarization.
Authors: Sun Yiting , Ma Yuanyuan , Tian Zhihua , Liu Xijuan , Yan Xiang , Zhao Wei , Wang Jie , Wang Zhijie 
Published: June 2022

e20552 Background: Missense alteration at EGFR L792F emerges after osimertinib resistance in patients with non-small cell lung cancer (NSCLC). However, its mechanism has not been sufficiently clarified. We aimed to explore the critical molecular events and coping strategies in osimertinib resistance due to acquired L792F mutation. Methods: Circulating tumor DNA-based sequencing data of 1382 patients with osimertinib resistance were collected to illustrate the prevalence of L792F mutation. Sensitivity to osimertinib was tested with constructed 19Del/T790M-cis-L792F mutations and control cell lines in vitro and in vivo. The correlation and linked pathways between M2 macrophage polarization and EGFR 19Del/T790M-cis-L792F-induced osimertinib resistance were investigated. Also, possible interventions to suppress osimertinib resistance by targeting IL-4 or STAT3 were explored. Results: The concomitant EGFR L792 was identified as an independent mutation following the acquisition of T790M after osimertinib resistance, in that 5 of the 946 patients with osimertinib resistance harbored EGFR L792F- cis mutation. Transfected EGFR 19Del/T790M-cis-L792F in cell lines had decreased sensitivity to osimertinib and enhanced infiltrating macrophage with M2 polarization. Silico analyses confirmed the role of M2 polarization in osimertinib resistance induced by EGFR T790M-cis-L792F mutations. The upregulated phosphorylation of STAT3 Tyr705 and downstream expression and secretion of IL-4 induced M2 polarization. Furthermore, blockade of STAT3/IL-4 (SH-4-54 or dupilumab) suppressed M2 macrophage polarization and regressed tumor sensitivity to osimertinib and delayed tumor growth. Conclusions: Our results provided solid evidence of EGFR T790M-cis-L792F mutation as a factor inducing osimertinib resistance. Targeting EGFR T790M-cis-L792F/STAT3 Tyr705/IL-4 pathway could be a potential strategy to suppress osimertinib resistance in NSCLC.
Tumor necrosis or cavity on baseline CT scan as a negative predictive biomarker for immune checkpoint inhibitors in advanced lung squamous cell carcinoma.
Authors: Long Feng , Lin Gen , Zheng Xinlong , Jiang Kan , Miao Qian 
Published: June 2022

e20556 Background: Current predictive biomarker for immune checkpoint inhibitors (ICIs) does not distinct according to histologic subtype. We hypothesize that necrosis or cavity on baseline CT scan in lung squamous cell carcinoma (LSCC) is predictive of treatment for ICIs. Methods: This was a multicenter retrospective analysis of patients with advanced LSCC. All eligible patients must had received either first-line chemotherapy only (chemotherapy group), or ICIs as monotherapy or combined with chemotherapy (ICIs group). Radiotherapy to thorax was not allowed. Baseline contrast-enhanced CT were reviewed by independent radiologist in each center. Radiologic finding was correlated with outcomes. Results: Total of 538 patients were eligible with 270 patients in the chemotherapy group and 268 patients in ICIs group. Baseline characteristics were well balanced. Tumor necrosis or cavity was identified in 111 (41.1%) in chemotherapy group and 99 (36.9%) in ICIs group. In chemotherapy group, there was no difference in PFS between patients with or without necrosis or cavity (5.33 vs 4.97 months, Hazard Ratio (HR) 1.05, 95% confidence interval (CI), 0.81-1.36, p= 0.726). In contrast, there was significant difference in PFS in ICIs group favoring patients without tumor necrosis or cavity (8.7 vs 6.5 months, HR 0.67, 95% CI 0.42–0.63, p< 0.001). Multivariate Cox analysis confirmed necrosis or cavity as an independent unfavorable predictive factor for PFS (HR 0.68; 95% CI, 0.51-0.9; p= 0.007). Conclusions: Tumor necrosis or cavity on baseline chest CT scan is a promising predictive biomarker for ICIs in LSCC, and this observation warrant further investigation.
The impact of EGFR Exon 20 mutation subtypes on lung cancer prognosis.
Authors: Xu Ming , Li Yingmei , Liu Danni , Mu Tianhao , Cheng Nitao 
Published: June 2022

e20557 Background: Many lung cancer patients with epidermal growth factor receptor (EGFR) mutations benefit from tyrosine kinase inhibitors (TKIs). However, patients with EGFR exon 20 mutations usually have worse response rates than other types of EGFR mutations. Here we investigated how different mutation subtypes of EGFR exon 20 affected the prognosis. Methods: Clinical and genomic data from 3 studies (MSKCC2020, MSKCC2021, and OncoSG) of patients with lung adenocarcinoma (LUAD) were reviewed (n = 1,001). Four hundred and seventeen patients harbored EGFR mutations and 52 of them had EGFR exon 20 mutations. The correlation of mutation subtypes with OS data was analyzed using R package. Results: In lung cancer patients with EGFR mutations (n = 417), 52 of them (12.5%) had a total of 64 EGFR exon 20 mutations, and could be categorized into 16 different subtypes, with top 5 subtypes being T790M (n = 28), S768I (n = 8), C797S (n = 7), A767_V769dup (n = 6) and S768_D770dup (n = 3). Patients with S768I (p = 0.0038) and A767_V769dup (p = 0.03) were found to have significantly worse OS than patients without these mutations by log-rank test. EGFR T790M, which was the most prevalent exon 20 mutation in these patients, did not present significant correlation in survival analysis. Conclusions: Although patients with EGFR exon 20 mutations accounted for only about 5% LUAD patients, and had worse response rates in general, certain subtypes had significantly different prognoses compared with other subtypes.
Neoadjuvant chemo-immunotherapy increases tumor immune lymphocytes infiltration in resectable NSCLC.
Authors: Li Ziming , Chen Tianxiang , Wen Fengcai , Zhang Ding , Chen Yanan , Zhao Xiaochen 
Published: June 2022

e20573 Background: NCIT (neoadjuvant Chemo-immunotherapy treatment) has revolutionized the treatment of resectable NSCLC due to its better MPR (major pathologic response) rate and pCR (pathologic complete response) rate over neoadjuvant chemotherapy or immunotherapy. However, the intrinsic mechanism underlying this treatment remains unclear. In recent years, the immune microenvironment has attracted considerable attention in the field of immunotherapy. In this study, we explored the relationship between tumor immune lymphocytes (TILs), tertiary lymphoid structures (TLS), and response to NCIT in resectable NSCLC and the change in TILs before and after NCIT. Methods: Twenty-five patients with stage IIA-IIIC NSCLC who underwent surgery after NCIT were enrolled in this retrospective study. Multiplex immunofluorescence (mIF) staining and image analysis assays were performed on the samples collected before and after NCIT for each patient. Results: Among the enrolled patients, 10 achieved MPR or pCR which were defined as response group, whereas 15 did not respond well to NCIT which were defined as non-response group. The results of the mIF assays revealed that NCIT was associated with an increase in immune lymphocytes, including CD3+ (tumor, p = 0.23; stroma, p < 0.01), CD4+ (tumor, p = 0.011; stroma, p < 0.001), CD4+Foxp3+ (tumor, p = 0.63; stroma, p < 0.001), CD8+ (tumor, p = 0.00031; stroma, p < 0.001), CD8+PD-1+ (tumor, p = 0.13; stroma, p = 0.022), PD-L1+CD68+ (tumor, p = 0.85; stroma, p = 0.041), and TLS (tertiary lymphoid structures, p = 0.00027). The comparison of TIL between response group and non-response group revealed that CD3, FOXP3+, and CD8+PD-1+ may serve as predictors of the response to neoadjuvant immunotherapy. Conclusions: To our knowledge, this is the first study to explore the relationship between TILs, TLS, and response to NCIT and TIL changes during NCIT in resectable Chinese NSCLC. In resectable NSCLC, the infiltration of immune cells before NCIT was correlated with the pathologic complete response, which enhanced the TILs as a promising predictor for selecting patients who were more likely to benefit from NCIT.
Automated imaging-based prognostication (IPRO) for stage I non-small cell lung cancer using deep learning applied to computed tomography.
Authors: Torres Felipe Soares , Akbar Shazia , Raman Srinivas , Yasufuku Kazuhiro , Hannessy Thomas Jay , Baldauf-Lenschen Felix , Leighl Natasha B. 
Published: June 2022

e20575 Background: Computed tomography (CT) imaging is used to inform staging and treatment decisions for stage I non-small cell lung cancer (NSCLC) patients. We have previously used deep learning applied to pretreatment CTs to generate an imaging-based prognostication (IPRO) score that automatically quantifies mortality risk and stratifies patients beyond tumor, node, metastasis (TNM) substages. Here we present validation data of its prognostic impact. Methods: We developed a fully automated deep learning model, IPRO, designed to process a CT scan, localize the 36cm3 space centered on the lungs, and learn prognostic imaging features to predict mortality risk. IPRO was trained on pretreatment CTs acquired from 1,696 patients treated for NSCLC at a tertiary care center between 2004 and 2018. We withheld 20% of the cases for validation, including 162 patients that were diagnosed with stage I NSCLC by clinical staging. We evaluated IPRO’s ability to stratify stage I NSCLC patients into mortality risk quintiles using the Cox proportional hazards model and assessed differences in median overall survival (mOS). Results: Of the 162 stage I NSCLC patients in the validation set, the mOS was 68.5 months (95% CI 66.7-69.6), 85 (52.5%) were male, and 125 (77.2%) were diagnosed with stage IA. Of these, 111 patients received surgery, 40 received radiotherapy (RT), 9 received surgery + adjuvant systemic therapy (ST), and 2 patients received surgery + ST + RT. According to IPRO, the patients predicted to have the highest risk had significantly increased 5-year mortality compared to those predicted to have the lowest risk (OR 8.4, 95% CI 2.4-29.2, p < 0.01); median survival 48.0 months and 69.5 months, respectively. Conclusions: Deep learning applied to pretreatment CTs provides personalized prognostic insights for stage I NSCLC beyond current TNM staging. [Table: see text]
Efficacy and safety of second-line (2L) therapy in patients with relapsed small cell lung cancer (SCLC): A systematic literature review (SLR).
Authors: Nair Abhishek A. , Kwon Christina S. , Harricharan Sharada , Zhang Xinke 
Published: June 2022

e20576 Background: Although SCLC is sensitive to first-line chemotherapy, most patients experience relapse, and options for 2L therapy are limited. Patients with relapsed SCLC have a poor prognosis, particularly those with resistant disease. To better understand the clinical unmet need of relapsed SCLC, we conducted a SLR of the efficacy and safety of currently approved 2L treatments for SCLC. Methods: EMBASE, MEDLINE, Cochrane databases (01/1990-11/2021), and congress abstracts (2020-21) were queried in accordance with the Preferred Reporting Item for Systematic Reviews and Meta-Analyses (PRISMA) guidelines using Population, Intervention & Comparators, Outcomes and Study Design (PICOS) criteria to identify interventional studies involving 2L SCLC treatments. Efficacy and safety data were extracted in overall populations (O), as well as platinum-sensitive (S) and resistant (R) subgroups. Efficacy data including overall survival (OS), progression-free survival (PFS), overall response rate (ORR), and duration of response (DoR) were summarized for currently approved treatments including topotecan (T), amrubicin (A), and lurbinectedin (L) monotherapies. Results: Of the 4,329 records identified, 130 studies were selected, of which 35 studies investigated T (22 studies), A (15 studies) and L (1 study) monotherapies (3 studies comparing A vs T) and outcomes by these treatments are presented (Table). Median OS ranged from 5.0 to 12.0 months in O, 3.4 to 11.0 in R, and 5.0 to 14.4 months in S. Median PFS was up to 4 months in O and R. ORR ranged widely by treatments. Median DoR was 3.1 to 5.3 months in O, less than 5 months in R, and 10 months in S. Among studies reporting overall safety, grade 3+ adverse events (AEs) were observed in 72%-96% and 74%-93% of patients with T (n = 308 from 3 studies) and A (n = 526 from 3 studies), respectively. The most common grade 3+ AEs in patients with L (n = 105) were neutropenia (46%) followed by leucopenia (29%). Conclusions: Relapsed SCLC patients treated with currently approved treatments have poor survival outcomes, especially those with resistant disease. A significant unmet need exists for treatment options extending survival and durability.[Table: see text]