DataSheet_1_Stemness Refines the Classification of Colorectal Cancer With Stratified Prognosis, Multi-Omics Landscape, Potential Mechanisms, and Treatment Options.docx

BackgroundStemness refers to the capacities of self-renewal and repopulation, which contributes to the progression, relapse, and drug resistance of colorectal cancer (CRC). Mounting evidence has established the links between cancer stemness and intratumoral heterogeneity across cancer. Currently, the intertumoral heterogeneity of cancer stemness remains elusive in CRC.MethodsThis study enrolled four CRC datasets, two immunotherapy datasets, and a clinical in-house cohort. Non-negative matrix factorization (NMF) was performed to decipher the heterogeneity of cancer stemness. Multiple machine learning algorithms were applied to develop a nine-gene stemness cluster predictor. The clinical outcomes, multi-omics landscape, potential mechanisms, and immune features of the stemness clusters were further explored.ResultsBased on 26 published stemness signatures derived by alternative approaches, we decipher two heterogeneous clusters, low stemness cluster 1 (C1) and high stemness cluster 2 (C2). C2 possessed a higher proportion of advanced tumors and displayed worse overall survival and relapse-free survival compared with C1. The MSI-H and CMS1 tumors tended to enrich in C1, and the mesenchymal subtype CMS4 was the prevalent subtype of C2. Subsequently, we developed a nine-gene stemness cluster predictor, which robustly validated and reproduced our stemness clusters in three independent datasets and an in-house cohort. C1 also displayed a generally superior mutational burden, and C2 possessed a higher burden of copy number deletion. Further investigations suggested that C1 enriched numerous proliferation-related biological processes and abundant immune infiltration, while C2 was significantly associated with mesenchyme development and differentiation. Given results derived from three algorithms and two immunotherapeutic cohorts, we observed C1 could benefit more from immunotherapy. For patients with C2, we constructed a ridge regression model and further identified nine latent therapeutic agents, which might improve their clinical outcomes.ConclusionsThis study proposed two stemness clusters with stratified prognosis, multi-omics landscape, potential mechanisms, and treatment options. Current work not only provided new insights into the heterogeneity of cancer stemness, but also shed light on optimizing decision-making in immunotherapy and chemotherapy.</p

DataSheet_2_Stemness Refines the Classification of Colorectal Cancer With Stratified Prognosis, Multi-Omics Landscape, Potential Mechanisms, and Treatment Options.xlsx

BackgroundStemness refers to the capacities of self-renewal and repopulation, which contributes to the progression, relapse, and drug resistance of colorectal cancer (CRC). Mounting evidence has established the links between cancer stemness and intratumoral heterogeneity across cancer. Currently, the intertumoral heterogeneity of cancer stemness remains elusive in CRC.MethodsThis study enrolled four CRC datasets, two immunotherapy datasets, and a clinical in-house cohort. Non-negative matrix factorization (NMF) was performed to decipher the heterogeneity of cancer stemness. Multiple machine learning algorithms were applied to develop a nine-gene stemness cluster predictor. The clinical outcomes, multi-omics landscape, potential mechanisms, and immune features of the stemness clusters were further explored.ResultsBased on 26 published stemness signatures derived by alternative approaches, we decipher two heterogeneous clusters, low stemness cluster 1 (C1) and high stemness cluster 2 (C2). C2 possessed a higher proportion of advanced tumors and displayed worse overall survival and relapse-free survival compared with C1. The MSI-H and CMS1 tumors tended to enrich in C1, and the mesenchymal subtype CMS4 was the prevalent subtype of C2. Subsequently, we developed a nine-gene stemness cluster predictor, which robustly validated and reproduced our stemness clusters in three independent datasets and an in-house cohort. C1 also displayed a generally superior mutational burden, and C2 possessed a higher burden of copy number deletion. Further investigations suggested that C1 enriched numerous proliferation-related biological processes and abundant immune infiltration, while C2 was significantly associated with mesenchyme development and differentiation. Given results derived from three algorithms and two immunotherapeutic cohorts, we observed C1 could benefit more from immunotherapy. For patients with C2, we constructed a ridge regression model and further identified nine latent therapeutic agents, which might improve their clinical outcomes.ConclusionsThis study proposed two stemness clusters with stratified prognosis, multi-omics landscape, potential mechanisms, and treatment options. Current work not only provided new insights into the heterogeneity of cancer stemness, but also shed light on optimizing decision-making in immunotherapy and chemotherapy.</p

A Bioinspired Skin UV Filter with Broadband UV Protection, Photostability, and Resistance to Oxidative Damage

In recent years, sunscreens’ adverse impacts on the environment and biology have gained wide attention. The improvement of sunscreen safety has become one of the major priorities in skin photoprotection research. It is an effective strategy to develop bionic photoprotective materials by simulating the photoprotective mechanism existing in nature. Inspired by the photoprotective mechanisms of skin and plant leaves, the bionic photoprotective material CS-SA-PDA nanosheet was developed using the free radical grafting method and Michael addition, with natural melanin analogue polydopamine (PDA) nanoparticles and plant sunscreen molecular sinapic acid (SA) as sun protection factors and natural polymer chitosan (CS) as the connecting arm. The results show that CS-SA-PDA can effectively shield UVB and UVA due to the possible synergistic effect between PDA and SA. The introduction of polymer CS significantly improved the photostability of SA and reduced the skin permeability of PDA nanoparticles. The CS-SA-PDA nanosheet can also effectively scavenge photoinduced free radicals. Furthermore, in vivo toxicity and anti-UV evaluations confirm that CS-SA-PDA has no skin irritation and is excellent against skin photodamage, which makes it an ideal skin photoprotective material

Insight Investigation of Active Palladium Surface Sites in Palladium-Ceria Catalysts for NO + CO Reaction

The palladium species in ceria-based catalysts have a significant influence on their catalytic performance. In this work, the structure evolution of palladium species induced by various calcination rate was investigated and then these calcined catalysts were applied to NO + CO catalytic reaction. Systematic investigations by various measurements demonstrate that the calcination rate and catalytic process play crucial roles on the formation ways of palladium species and identify the forms of active palladium surface sites for NO + CO reaction. Results indicate that the calcination process resulted in the formation of three types of palladium components: PdO interacted with ceria supports (PdO_<i>x</i>/Pd–O–Ce cluster), PdO nanoparticles on the surface, and Pd²⁺ ions incorporated into the subsurface lattice (Pd–O–Ce solid solution). It is also proven that the state and distribution of palladium components are dependent on the calcination rate: rapid calcination rate is beneficial for the generation of PdO species (PdO_<i>x</i>/Pd–O–Ce and PdO), while slow calcination rate makes contribution to the formation of Pd–O–Ce. Furthermore, the subsequent catalytic process could induce the decomposition of PdO_<i>x</i>/Pd–O–Ce and formation of more fractions of active Pd species in PdO oxide phase. On the basis of the catalytic performances, we found the superior catalytic properties are detected for catalysts containing 0.5% Pd (0.5% is corresponding to the palladium content in molar ratio) with fast calcination rate. This is due to the synergistic effect of active Pd in PdO decomposed form PdO_<i>x</i>/Pd–O–Ce in the catalytic process and the palladium ions in Pd–O–Ce solid solution

Image_2_ALOX12: A Novel Insight in Bevacizumab Response, Immunotherapy Effect, and Prognosis of Colorectal Cancer.jpeg

Colorectal cancer is a highly malignant cancer with poor prognosis and mortality rates. As the first biological agent approved for metastatic colorectal cancer (mCRC), bevacizumab was confirmed to exhibit good performance when combined with chemotherapy and immunotherapy. However, the efficacy of both bevacizumab and immunotherapy is highly heterogeneous across CRC patients with different stages. Thus, exploring a novel biomarker to comprehensively assess the prognosis and bevacizumab and immunotherapy response of CRC is of great significance. In our study, weighted gene co-expression network analysis (WGCNA) and the receiver operating characteristic (ROC) curves were employed to identify bevacizumab-related genes. After verification in four public cohorts and our internal cohort, ALOX12 was identified as a key gene related to bevacizumab response. Prognostic analysis and in vitro experiments further demonstrated that ALOX12 was closely associated with the prognosis, tumor proliferation, invasion, and metastasis. Multi-omics data analysis based on mutation and copy number variation (CNV) revealed that RYR3 drove the expression of ALOX12 and the deletion of 17p12 inhibited ALOX12 expression, respectively. Moreover, we interrogated the relationship between ALOX12 and immune cells and checkpoints. The results exhibited that high ALOX12 expression predicted a higher immune infiltration and better immunotherapy response, which was further validated in Tumor Immune Dysfunction and Exclusion (TIDE) and Subclass Mapping (SubMap) methods. Above all, our study provides a stable biomarker for clinical protocol optimization, prognostic assessment, precise treatment, and individualized treatment of CRC.</p

Image_3_ALOX12: A Novel Insight in Bevacizumab Response, Immunotherapy Effect, and Prognosis of Colorectal Cancer.jpeg

Colorectal cancer is a highly malignant cancer with poor prognosis and mortality rates. As the first biological agent approved for metastatic colorectal cancer (mCRC), bevacizumab was confirmed to exhibit good performance when combined with chemotherapy and immunotherapy. However, the efficacy of both bevacizumab and immunotherapy is highly heterogeneous across CRC patients with different stages. Thus, exploring a novel biomarker to comprehensively assess the prognosis and bevacizumab and immunotherapy response of CRC is of great significance. In our study, weighted gene co-expression network analysis (WGCNA) and the receiver operating characteristic (ROC) curves were employed to identify bevacizumab-related genes. After verification in four public cohorts and our internal cohort, ALOX12 was identified as a key gene related to bevacizumab response. Prognostic analysis and in vitro experiments further demonstrated that ALOX12 was closely associated with the prognosis, tumor proliferation, invasion, and metastasis. Multi-omics data analysis based on mutation and copy number variation (CNV) revealed that RYR3 drove the expression of ALOX12 and the deletion of 17p12 inhibited ALOX12 expression, respectively. Moreover, we interrogated the relationship between ALOX12 and immune cells and checkpoints. The results exhibited that high ALOX12 expression predicted a higher immune infiltration and better immunotherapy response, which was further validated in Tumor Immune Dysfunction and Exclusion (TIDE) and Subclass Mapping (SubMap) methods. Above all, our study provides a stable biomarker for clinical protocol optimization, prognostic assessment, precise treatment, and individualized treatment of CRC.</p

Image_1_ALOX12: A Novel Insight in Bevacizumab Response, Immunotherapy Effect, and Prognosis of Colorectal Cancer.jpeg

Colorectal cancer is a highly malignant cancer with poor prognosis and mortality rates. As the first biological agent approved for metastatic colorectal cancer (mCRC), bevacizumab was confirmed to exhibit good performance when combined with chemotherapy and immunotherapy. However, the efficacy of both bevacizumab and immunotherapy is highly heterogeneous across CRC patients with different stages. Thus, exploring a novel biomarker to comprehensively assess the prognosis and bevacizumab and immunotherapy response of CRC is of great significance. In our study, weighted gene co-expression network analysis (WGCNA) and the receiver operating characteristic (ROC) curves were employed to identify bevacizumab-related genes. After verification in four public cohorts and our internal cohort, ALOX12 was identified as a key gene related to bevacizumab response. Prognostic analysis and in vitro experiments further demonstrated that ALOX12 was closely associated with the prognosis, tumor proliferation, invasion, and metastasis. Multi-omics data analysis based on mutation and copy number variation (CNV) revealed that RYR3 drove the expression of ALOX12 and the deletion of 17p12 inhibited ALOX12 expression, respectively. Moreover, we interrogated the relationship between ALOX12 and immune cells and checkpoints. The results exhibited that high ALOX12 expression predicted a higher immune infiltration and better immunotherapy response, which was further validated in Tumor Immune Dysfunction and Exclusion (TIDE) and Subclass Mapping (SubMap) methods. Above all, our study provides a stable biomarker for clinical protocol optimization, prognostic assessment, precise treatment, and individualized treatment of CRC.</p

Table_1_ALOX12: A Novel Insight in Bevacizumab Response, Immunotherapy Effect, and Prognosis of Colorectal Cancer.xlsx

Colorectal cancer is a highly malignant cancer with poor prognosis and mortality rates. As the first biological agent approved for metastatic colorectal cancer (mCRC), bevacizumab was confirmed to exhibit good performance when combined with chemotherapy and immunotherapy. However, the efficacy of both bevacizumab and immunotherapy is highly heterogeneous across CRC patients with different stages. Thus, exploring a novel biomarker to comprehensively assess the prognosis and bevacizumab and immunotherapy response of CRC is of great significance. In our study, weighted gene co-expression network analysis (WGCNA) and the receiver operating characteristic (ROC) curves were employed to identify bevacizumab-related genes. After verification in four public cohorts and our internal cohort, ALOX12 was identified as a key gene related to bevacizumab response. Prognostic analysis and in vitro experiments further demonstrated that ALOX12 was closely associated with the prognosis, tumor proliferation, invasion, and metastasis. Multi-omics data analysis based on mutation and copy number variation (CNV) revealed that RYR3 drove the expression of ALOX12 and the deletion of 17p12 inhibited ALOX12 expression, respectively. Moreover, we interrogated the relationship between ALOX12 and immune cells and checkpoints. The results exhibited that high ALOX12 expression predicted a higher immune infiltration and better immunotherapy response, which was further validated in Tumor Immune Dysfunction and Exclusion (TIDE) and Subclass Mapping (SubMap) methods. Above all, our study provides a stable biomarker for clinical protocol optimization, prognostic assessment, precise treatment, and individualized treatment of CRC.</p

Additional file 1 of PI3K pathway mutation predicts an activated immune microenvironment and better immunotherapeutic efficacy in head and neck squamous cell carcinoma

Additional file 1: Fig. S1. Overall workflow diagram of our research. Fig. S2. Landscape and clinical prognostic value of PI3K pathway mutation in the MD-Anderson cohort as well as heatmaps of immune cells infiltration and boxplots of immunomodulators expression. (A) Oncoplot depicts the landscape of PI3K pathway gene mutation in the MD-Anderson cohort. (B) Multivariate Cox regression analysis of PI3K pathway mutation phenotype in the MD-Anderson cohort. (C-D) Kaplan-Meier survival analysis of OS (C) and DFS (D) between the PI3K pathway mutation and wild groups in the MD-Anderson cohort. (E-F) Assess infiltration abundance of 22 immune cells calculated by CIBERSORT (E) as well as 39 immune cells and stromal cells calculated by xCell (F). (G) Boxplots represent different expression levels of 18 ligand molecules between the two groups. WT, wild type; MT, mutant type; *P < 0.05. Fig. S3. The relationship between PI3K pathway mutation and HPV status and patient prognosis in the TCGA-HNSC cohort. (A) Boxplots represent different expression levels of 19 receptor molecules between the PI3K pathway mutation and wild groups. (B) Composition percentage of HPV status between the PI3K pathway mutation and wild groups. (C) Composition percentage of PI3K pathway mutation status between the HPV-negative and HPV-positive groups. (D) Kaplan-Meier survival analysis of the HPV status in the TCGA-HNSC cohort. (E) Kaplan-Meier survival analysis of PI3K pathway mutation in the HPV-negative group patients of TCGA-HNSC cohort. (F-G) Kaplan-Meier survival analysis of HPV status in the PI3K pathway wild (F) and mutation (G) group patients of TCGA-HNSC cohort. WT, wild type; MT, mutant type; *P < 0.05; **P < 0.01. Table S1. The 29 PI3K pathway genes used to define samples as PI3K pathway mutation or wild groups

Image_1_SCG2: A Prognostic Marker That Pinpoints Chemotherapy and Immunotherapy in Colorectal Cancer.jpeg

BackgroundFluorouracil (FU)-based chemotherapy regimens are indispensable in the comprehensive treatment of colorectal cancer (CRC). However, the heterogeneity of treated individuals and the severe adverse effects of chemotherapy results in limited overall benefit.MethodsFirstly, Weighted gene co-expression network analysis (WGCNA) identified modules tightly associated with chemotherapy response. Then, the in-house cohort and prognostic cohorts from TCGA and GEO were subjected to Cox proportional hazards model and survival analysis to ascertain the predictable function of SCG2 on the prognosis of CRC patients. Finally, we performed In vitro experiments, functional analysis, somatic mutation, and copy number variation research to explore the biological characteristics of SCG2.ResultsWe identified red and green as the modules most associated with chemotherapy response, in which SCG2 was considered a risky factor with higher expression predicting poorer prognosis. SCG2 expression in the APC non-mutation group was remarkably higher than in the mutation group. The mutation frequencies of amplified genes differed significantly between different SCG2 expression subgroups. Besides, CRC cell lines with SCG2 knockdown have reduced invasive, proliferative, and proliferative capacity. We discovered that the SCG2 high expression subgroup was the immune hot type and considered more suitable for immunotherapy.ConclusionThis study demonstrates the clinical significance and biological characteristics of SCG2, which could serve as a promising biomarker to identify patients who may benefit from chemotherapy and immunotherapy.</p