Table1_Transcriptomic analysis of oxidative stress mechanisms induced by acute nanoplastic exposure in Sepia esculenta larvae.DOCX

Nanoplastics (NPs), as a new type of pollutant with a size small than 1 μm, are ubiquitous and harmful to organisms. There has been an increasing amount of research concerning the effects of NPs on organisms over recent years, especially on aquatic animals. However, there is a limited study on the impact of NPs on mollusk cephalopods. In this research, Sepia esculenta, belonging to Cephalopoda, Coleoidea, Sepioidea, was selected to explore the effects caused by NPs exposure. The S. esculenta larvae were exposed to polystyrene NPs (PS-NPs) with diameter 50 nm (100 mg/L) for 4 h. The detection of oxidative stress biomarkers displayed an obvious increase in SOD (superoxide dismutase) activity and MDA (malondialdehyde) level. Then, RNA-Seq was performed to explore the oxidative stress response at mRNA level. The transcriptome analysis demonstrated that the expression of 2,570 genes was affected by PS-NPs. Besides, the signaling pathways of ribosome, ribosome biogenesis in eukaryotes, proteasome, and MAPK were enriched. This study not only provides novel references for understanding the mechanisms of oxidative stress response induced by NPs, but also reminds us to follow with interest the influence of acute exposure to NPs.</p

sj-xlsx-2-slr-10.1177_02676583221128520 – Supplemental material for Testing the Bottleneck Hypothesis: Chinese EFL learners’ knowledge of morphology and syntax across proficiency levels

Supplemental material, sj-xlsx-2-slr-10.1177_02676583221128520 for Testing the Bottleneck Hypothesis: Chinese EFL learners’ knowledge of morphology and syntax across proficiency levels by Shiyu Wu, Dilin Liu and Zan Li in Second Language Research</p

sj-docx-1-slr-10.1177_02676583221128520 – Supplemental material for Testing the Bottleneck Hypothesis: Chinese EFL learners’ knowledge of morphology and syntax across proficiency levels

Supplemental material, sj-docx-1-slr-10.1177_02676583221128520 for Testing the Bottleneck Hypothesis: Chinese EFL learners’ knowledge of morphology and syntax across proficiency levels by Shiyu Wu, Dilin Liu and Zan Li in Second Language Research</p

Image_7_Cancer-associated fibroblasts-derived lncRNA signature as a putative biomarker in breast cancer.pdf

Long noncoding RNAs (lncRNAs) have been reported to play a key role in regulating tumor microenvironment and immunity. Cancer-associated fibroblasts (CAFs) are abundant in many tumors. However, the functional and clinical significance of lncRNAs specifically expressed in CAFs has not been fully elucidated. In this study, we identified a list of 95 CAF-specific lncRNAs (FibLnc), including HHLA3, TP53TG1, ST7-AS1, LINC00536, ZNF503-AS1, MIR22HG, and MAPT-AS1, based on immune cell transcriptome expression profiling data. Based on the Cancer Genome Atlas and Gene Expression Omnibus datasets, we found that the FibLnc score predicted differences in overall patient survival and performed well in multiple datasets. FibLnc score was associated with the clinical stage of patients with breast cancer but did not significantly correlate with the PAM50 classification. Functional analysis showed that FibLnc was positively correlated with signaling pathways associated with malignant tumor progression. In addition, FibLnc was positively correlated with tumor mutational load and could predict immunotherapy response in patients with breast cancer receiving anti-PD-1 or anti-CTLA4 therapy. Our proposed FibLnc score was able to reflect the status of the immune environment and immunotherapeutic response in breast cancer, which could help explore potential therapeutic decisions and regulatory mechanisms of CAF-specific lncRNAs.</p

Table_6_Cancer-associated fibroblasts-derived lncRNA signature as a putative biomarker in breast cancer.xlsx

Long noncoding RNAs (lncRNAs) have been reported to play a key role in regulating tumor microenvironment and immunity. Cancer-associated fibroblasts (CAFs) are abundant in many tumors. However, the functional and clinical significance of lncRNAs specifically expressed in CAFs has not been fully elucidated. In this study, we identified a list of 95 CAF-specific lncRNAs (FibLnc), including HHLA3, TP53TG1, ST7-AS1, LINC00536, ZNF503-AS1, MIR22HG, and MAPT-AS1, based on immune cell transcriptome expression profiling data. Based on the Cancer Genome Atlas and Gene Expression Omnibus datasets, we found that the FibLnc score predicted differences in overall patient survival and performed well in multiple datasets. FibLnc score was associated with the clinical stage of patients with breast cancer but did not significantly correlate with the PAM50 classification. Functional analysis showed that FibLnc was positively correlated with signaling pathways associated with malignant tumor progression. In addition, FibLnc was positively correlated with tumor mutational load and could predict immunotherapy response in patients with breast cancer receiving anti-PD-1 or anti-CTLA4 therapy. Our proposed FibLnc score was able to reflect the status of the immune environment and immunotherapeutic response in breast cancer, which could help explore potential therapeutic decisions and regulatory mechanisms of CAF-specific lncRNAs.</p

Table_4_Cancer-associated fibroblasts-derived lncRNA signature as a putative biomarker in breast cancer.xlsx

Long noncoding RNAs (lncRNAs) have been reported to play a key role in regulating tumor microenvironment and immunity. Cancer-associated fibroblasts (CAFs) are abundant in many tumors. However, the functional and clinical significance of lncRNAs specifically expressed in CAFs has not been fully elucidated. In this study, we identified a list of 95 CAF-specific lncRNAs (FibLnc), including HHLA3, TP53TG1, ST7-AS1, LINC00536, ZNF503-AS1, MIR22HG, and MAPT-AS1, based on immune cell transcriptome expression profiling data. Based on the Cancer Genome Atlas and Gene Expression Omnibus datasets, we found that the FibLnc score predicted differences in overall patient survival and performed well in multiple datasets. FibLnc score was associated with the clinical stage of patients with breast cancer but did not significantly correlate with the PAM50 classification. Functional analysis showed that FibLnc was positively correlated with signaling pathways associated with malignant tumor progression. In addition, FibLnc was positively correlated with tumor mutational load and could predict immunotherapy response in patients with breast cancer receiving anti-PD-1 or anti-CTLA4 therapy. Our proposed FibLnc score was able to reflect the status of the immune environment and immunotherapeutic response in breast cancer, which could help explore potential therapeutic decisions and regulatory mechanisms of CAF-specific lncRNAs.</p

Table_1_Cancer-associated fibroblasts-derived lncRNA signature as a putative biomarker in breast cancer.xlsx

Long noncoding RNAs (lncRNAs) have been reported to play a key role in regulating tumor microenvironment and immunity. Cancer-associated fibroblasts (CAFs) are abundant in many tumors. However, the functional and clinical significance of lncRNAs specifically expressed in CAFs has not been fully elucidated. In this study, we identified a list of 95 CAF-specific lncRNAs (FibLnc), including HHLA3, TP53TG1, ST7-AS1, LINC00536, ZNF503-AS1, MIR22HG, and MAPT-AS1, based on immune cell transcriptome expression profiling data. Based on the Cancer Genome Atlas and Gene Expression Omnibus datasets, we found that the FibLnc score predicted differences in overall patient survival and performed well in multiple datasets. FibLnc score was associated with the clinical stage of patients with breast cancer but did not significantly correlate with the PAM50 classification. Functional analysis showed that FibLnc was positively correlated with signaling pathways associated with malignant tumor progression. In addition, FibLnc was positively correlated with tumor mutational load and could predict immunotherapy response in patients with breast cancer receiving anti-PD-1 or anti-CTLA4 therapy. Our proposed FibLnc score was able to reflect the status of the immune environment and immunotherapeutic response in breast cancer, which could help explore potential therapeutic decisions and regulatory mechanisms of CAF-specific lncRNAs.</p

Table_2_Cancer-associated fibroblasts-derived lncRNA signature as a putative biomarker in breast cancer.xlsx

Long noncoding RNAs (lncRNAs) have been reported to play a key role in regulating tumor microenvironment and immunity. Cancer-associated fibroblasts (CAFs) are abundant in many tumors. However, the functional and clinical significance of lncRNAs specifically expressed in CAFs has not been fully elucidated. In this study, we identified a list of 95 CAF-specific lncRNAs (FibLnc), including HHLA3, TP53TG1, ST7-AS1, LINC00536, ZNF503-AS1, MIR22HG, and MAPT-AS1, based on immune cell transcriptome expression profiling data. Based on the Cancer Genome Atlas and Gene Expression Omnibus datasets, we found that the FibLnc score predicted differences in overall patient survival and performed well in multiple datasets. FibLnc score was associated with the clinical stage of patients with breast cancer but did not significantly correlate with the PAM50 classification. Functional analysis showed that FibLnc was positively correlated with signaling pathways associated with malignant tumor progression. In addition, FibLnc was positively correlated with tumor mutational load and could predict immunotherapy response in patients with breast cancer receiving anti-PD-1 or anti-CTLA4 therapy. Our proposed FibLnc score was able to reflect the status of the immune environment and immunotherapeutic response in breast cancer, which could help explore potential therapeutic decisions and regulatory mechanisms of CAF-specific lncRNAs.</p

Image_5_Cancer-associated fibroblasts-derived lncRNA signature as a putative biomarker in breast cancer.pdf

Long noncoding RNAs (lncRNAs) have been reported to play a key role in regulating tumor microenvironment and immunity. Cancer-associated fibroblasts (CAFs) are abundant in many tumors. However, the functional and clinical significance of lncRNAs specifically expressed in CAFs has not been fully elucidated. In this study, we identified a list of 95 CAF-specific lncRNAs (FibLnc), including HHLA3, TP53TG1, ST7-AS1, LINC00536, ZNF503-AS1, MIR22HG, and MAPT-AS1, based on immune cell transcriptome expression profiling data. Based on the Cancer Genome Atlas and Gene Expression Omnibus datasets, we found that the FibLnc score predicted differences in overall patient survival and performed well in multiple datasets. FibLnc score was associated with the clinical stage of patients with breast cancer but did not significantly correlate with the PAM50 classification. Functional analysis showed that FibLnc was positively correlated with signaling pathways associated with malignant tumor progression. In addition, FibLnc was positively correlated with tumor mutational load and could predict immunotherapy response in patients with breast cancer receiving anti-PD-1 or anti-CTLA4 therapy. Our proposed FibLnc score was able to reflect the status of the immune environment and immunotherapeutic response in breast cancer, which could help explore potential therapeutic decisions and regulatory mechanisms of CAF-specific lncRNAs.</p

Table_7_Cancer-associated fibroblasts-derived lncRNA signature as a putative biomarker in breast cancer.xlsx

Long noncoding RNAs (lncRNAs) have been reported to play a key role in regulating tumor microenvironment and immunity. Cancer-associated fibroblasts (CAFs) are abundant in many tumors. However, the functional and clinical significance of lncRNAs specifically expressed in CAFs has not been fully elucidated. In this study, we identified a list of 95 CAF-specific lncRNAs (FibLnc), including HHLA3, TP53TG1, ST7-AS1, LINC00536, ZNF503-AS1, MIR22HG, and MAPT-AS1, based on immune cell transcriptome expression profiling data. Based on the Cancer Genome Atlas and Gene Expression Omnibus datasets, we found that the FibLnc score predicted differences in overall patient survival and performed well in multiple datasets. FibLnc score was associated with the clinical stage of patients with breast cancer but did not significantly correlate with the PAM50 classification. Functional analysis showed that FibLnc was positively correlated with signaling pathways associated with malignant tumor progression. In addition, FibLnc was positively correlated with tumor mutational load and could predict immunotherapy response in patients with breast cancer receiving anti-PD-1 or anti-CTLA4 therapy. Our proposed FibLnc score was able to reflect the status of the immune environment and immunotherapeutic response in breast cancer, which could help explore potential therapeutic decisions and regulatory mechanisms of CAF-specific lncRNAs.</p