Identification and quantification of immune infiltration landscape on therapy and prognosis in left- and right-sided colon cancer

Male breast cancer differs from female breast cancer in molecular features that affect prognoses and drug responses

BACKGROUND

Male breast cancer (MBC) is a rare malignancy with a worse prognosis than female breast cancer (FBC). Current MBC treatment strategies are based on those for FBC. However, molecular differences between MBC and FBC with respect to prognosis and drug responses remain unclear.

METHODS

After controlling for confounding factors with propensity score matching (PSM), differences between MBC and FBC were comprehensively analyzed using many types of data: survival, immune microenvironments, sex hormone responses, drug sensitivity, transcriptomes, genomes, epigenomes, and proteomes.

RESULTS

Overall survival (OS) and cancer-specific survival (CSS) were both worse for MBC than for FBC. Differentially expressed mRNAs were enriched in numerous cancer-related functions and pathways, with SPAG16 and STOX1 being as the most important prognosis-related mRNAs for MBC. Competing endogenous RNA (ceRNA) and transcription factor (TF)-mRNA regulatory networks contain potential prognostic genes. Nine genes had higher mutation frequencies in MBC than in FBC. MBC shows a comparatively poor response to immunotherapy, with five proteins that promote breast cancer progression being highly expressed in MBC. MBC may be more responsive than FBC to estrogen. We detected six United States Food and Drug Administration (FDA)-approved therapeutic target genes as being differentially expressed between MBC and FBC.

CONCLUSION

The poor prognosis of MBC compared to FBC is due to numerous molecular differences and resulting drug responses.

GJA4 expressed on cancer associated fibroblasts (CAFs)-A 'promoter' of the mesenchymal phenotype

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer worldwide. Connexin is a transmembrane protein involved in gap junctions (GJs) formation. Our previous study found that connexin 37 (Cx37), encoded by gap junction protein alpha 4 (GJA4), expressed on fibroblasts acts as a promoter of CRC and is closely related to epithelial-mesenchymal transition (EMT) and tumor immune microenvironment. However, to date, the mechanism concerning the malignancy of GJA4 in tumor stroma has not been studied.

METHODS

Hematoxylin-eosin (HE) and immunohistochemical (IHC) staining were used to validate the expression and localization of GJA4. Using single-cell analysis, enrichment analysis, spatial transcriptomics, immunofluorescence staining (IF), Sirius red staining, wound healing and transwell assays, western blotting (WB), Cell Counting Kit-8 (CCK8) assay and in vivo experiments, we investigated the possible mechanisms of GJA4 in promoting CRC.

RESULTS

We discovered that in CRC, GJA4 on fibroblasts is involved in promoting fibroblast activation and promoting EMT through a fibroblast-dependent pathway. Furthermore, GJA4 may act synergistically with M2 macrophages to limit T cell infiltration by stimulating the formation of an immune-excluded desmoplasic barrier. Finally, we found a significantly correlation between GJA4 and pathological staging (P < 0.0001) or D2 dimer (R = 0.03, P < 0.05).

CONCLUSION

We have identified GJA4 expressed on fibroblasts is actually a promoter of the tumor mesenchymal phenotype. Our findings suggest that the interaction between GJA4+ fibroblasts and M2 macrophages may be an effective target for enhancing tumor immunotherapy.

Tspan protein family: focusing on the occurrence, progression, and treatment of cancer

The Tetraspanins (Tspan) protein family, also known as the tetraspanin family, contains 33 family members that interact with other protein molecules such as integrins, adhesion molecules, and T cell receptors by forming dimers or heterodimers. The Tspan protein family regulates cell proliferation, cell cycle, invasion, migration, apoptosis, autophagy, tissue differentiation, and immune response. More and more studies have shown that Tspan proteins are involved in tumorigenesis, epithelial-mesenchymal transition, thrombosis, tumor stem cell, and exosome signaling. Some drugs and microRNAs can inhibit Tspan proteins, thus providing new strategies for tumor therapy. An in-depth understanding of the functions and regulatory mechanisms of the Tspan protein family, which can promote or inhibit tumor development, will provide new strategies for targeted interventions in the future.

Heterogeneous characterization of neutrophilic cells in head and neck cancers

BACKGROUND

Neutrophilic cells are among the most abundant immune populations within the head and neck tumor microenvironment (TME) and harbor multiple mechanisms of immunosuppression. Despite these important features, neutrophilic cells may be underrepresented in contemporary studies that aim to comprehensively characterize the immune landscape of the TME due to discrepancies in tissue processing and analysis techniques. Here, we review the role of pathologically activated neutrophilic cells within the TME and pitfalls of various approaches used to study their frequency and function in clinical samples.

METHODS

The literature was identified by searching PubMed for "immune landscape" and "tumor immune microenvironment" in combination with keywords describing solid tumor malignancies. Key publications that assessed the immune composition of solid tumors derived from human specimens were included. The tumor and blood processing methodologies in each study were reviewed in depth and correlated with the reported abundance of neutrophilic cells.

RESULTS

Neutrophilic cells do not survive cryopreservation, and many studies fail to identify and study neutrophilic cell populations due to cryopreservation of clinical samples for practical reasons. Additional single-cell transcriptomic studies filter out neutrophilic cells due to low transcriptional counts.

CONCLUSIONS

This report can help readers critically interpret studies aiming to comprehensively study the immune TME that fail to identify and characterize neutrophilic cells.

Construction of a prognostic model for lung adenocarcinoma based on m6A/m5C/m1A genes

BACKGROUND

Developing a prognostic model for lung adenocarcinoma (LUAD) that utilizes m6A/m5C/m1A genes holds immense importance in providing precise prognosis predictions for individuals.

METHODS

This study mined m6A/m5C/m1A-related differential genes in LUAD based on public databases, identified LUAD tumor subtypes based on these genes, and further built a risk prognostic model grounded in differential genes between subtypes. The immune status between high- and low-risk groups was investigated, and the distribution of feature genes in tumor immune cells was analyzed using single-cell analysis. Based on the expression levels of feature genes, a projection of chemotherapeutic and targeted drugs was made for individuals identified as high-risk. Ultimately, cell experiments were further verified.

RESULTS

The 6-gene risk prognosis model based on differential genes between tumor subtypes had good predictive performance. Individuals classified as low-risk exhibited a higher (P < 0.05) abundance of infiltrating immune cells. Feature genes were mainly distributed in tumor immune cells like CD4+T cells, CD8+T cells, and regulatory T cells. Four drugs with relatively low IC50 values were found in the high-risk group: Elesclomol, Pyrimethamine, Saracatinib, and Temsirolimus. In addition, four drugs with significant positive correlation (P < 0.001) between IC50 values and feature gene expression were found, including Alectinib, Estramustine, Brigatinib, and Elesclomol. The low expression of key gene NTSR1 reduced the IC50 value of irinotecan.

CONCLUSION

Based on the m6A/m5C/m1A-related genes in LUAD, LUAD patients were divided into 2 subtypes, and a m6A/m5C/m1A-related LUAD prognostic model was constructed to provide a reference for the prognosis prediction of LUAD.

Tertiary lymphoid structures predict survival and response to neoadjuvant therapy in locally advanced rectal cancer

Tertiary lymphoid structure (TLS) contributes to the anti-tumor immune response, and predicts the prognosis of colorectal cancer patients. However, the potential impact of TLS in shaping the immune status of rectal adenocarcinoma, and the intrinsic relationship between TLS and neoadjuvant therapies (neoTx) remain unclear. We performed hematoxylin-eosin staining, immunohistochemical and biomolecular analyses to investigate TLS and tumor-infiltrating lymphocytes (TILs) in 221 neoTx-treated and 242 treatment-naïve locally advanced rectal cancer (LARC) patients. High TLS density was significantly associated with the absence of vascular invasion, a lower neutrophil-to-lymphocyte ratio, increased TLS maturity, a longer recurrence-free survival (RFS) (hazard ratio [HR] 0.2985 95% confidence interval [CI] 0.1894-0.4706, p < 0.0001) and enhanced infiltration of adaptive immune cells. Biomolecular analysis showed that high TLS-score was strongly associated with more infiltration of immune cells and increased activation of immune-related pathways. TLS+ tumors in pre-treatment specimens were associated with a higher proportion of good respond (62.5% vs. 29.8%, p < 0.0002) and pathological complete remission (pCR) (40.0% vs. 11.1%, p < 0.0001), and significantly increased RFS (HR 0.3574 95%CI 0.1489-0.8578 p = 0.0213) compared with TLS- tumors in the neoTx cohort, which was confirmed in GSE119409 and GSE150082. Further studies showed that neoTx significantly reduced TLS density and maturity, and abolished the prognostic value of TLS. Our study illustrates that TLS may have a key role in mediating the T-cell-inflamed tumor microenvironment, which also provides a new direction for neoTx, especially neoadjuvant immunotherapy, in LRAC patients.

Regulator of G protein signaling-1 regulates immune infiltration and macrophage polarization in clear cell renal cell carcinoma

OBJECTIVE

To better understand how to clear cell renal cell cancer (ccRCC) is affected by the regulator of G protein signaling-1 (RGS1), its effect on immune infiltration, macrophage polarization, tumor proliferation migration, and to explore whether RGS1 may serve as a marker and therapeutic target for ccRCC.

PATIENTS AND METHODS

In this study, a total of 20 surgical specimens of patients with pathological diagnosis of ccRCC admitted to the Department of Urology of the Second Affiliated Hospital of Anhui Medical University from November 2021 to June 2022 were selected for pathological and protein testing, while the expression of RGS1 in tumors, immune infiltration, and macrophage polarization, particularly M2 macrophage linked to the development of tumor microenvironment (TME), were combined with TGCA database and GO analysis. We also further explored and studied the expression and function of RGS1 in TME, investigated how RGS1 affected tumor growth, migration, apoptosis, and other traits, and initially explored the signaling pathways and mechanisms that RGS1 may affect.

RESULTS

RGS1 was found to be expressed at higher quantities in ccRCC than in normal cells or tissues, according to bioinformatics analysis and preliminary experimental data from this work. Using the TCGA database and GO analysis to describe the expression of RGS1 in a range of tumors, it was found that ccRCC had a much higher level of RGS1 expression than other tumor types. The results of gene enrichment analysis indicated that overexpression of RGS1 may be associated with immune infiltration. The outcomes of in vitro tests revealed that RGS1 overexpression in ccRCC did not significantly alter the proliferation and migration ability of ccRCC, but RGS1 overexpression promoted apoptosis in ccRCC. By in vitro co-culture experiments, RGS1 overexpression inhibited M2 macrophage polarization and also suppressed the Jagged-1/Notch signaling pathway.

CONCLUSIONS

RGS1 is highly expressed in ccRCC, while overexpression of RGS1 may increase immune infiltration in the TME and reduce the polarization of M2 macrophages while promoting apoptosis in ccRCC.

Identification of TTC21A as a Potential Prognostic Marker in Head and Neck Squamous Cell Carcinoma: In Silico Analysis

BACKGROUND/AIM

Tetratricopeptide repeat domain 21A (TTC21A) plays a crucial role in ciliary function and has been associated with various pathogenic processes, including carcinogenesis. However, its role in head and neck squamous cell carcinoma (HNSCC) has not been elucidated.

MATERIALS AND METHODS

Based on the sequencing and microarray data of HNSCC from publicly available databases, the expression of TTC21A was compared between different subgroups based on clinical and molecular parameters. The survival analysis and regression analysis were conducted using the Kaplan-Meier method and the Cox method, respectively. Functional analysis was performed by the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and gene set enrichment analysis (GSEA) tools. Immune infiltration analysis was performed based on the expression of TTC21A.

RESULTS

TTC21A decreased in tumor tissues and was associated with N stage, histologic grade, HPV infection, and TP53 mutation in HNSCC. TTC21A was an independent indicator of overall survival for patients with HNSCC. A high level of TTC21A expression indicated a favorable prognosis. The TTC21A expression level was involved with immune-related signaling regulation, immune-related gene expression, and immune cell infiltration. TTC21A expression was potent in predicting immunotherapeutic benefits.

CONCLUSION

TTC21A, as a potential predictor of favorable outcomes and immunotherapy response for HNSCC, is related to immune-related signaling regulation, immune-related gene expression, and immune cell infiltration.

Comprehensive Characterization of HATs and HDACs in Human Cancers Reveals Their Role in Immune Checkpoint Blockade

Histone acetylation that controlled by two mutually antagonistic enzyme families, histone acetyl transferases (HATs) and histone deacetylases (HDACs), as one of major epigenetic mechanisms controls transcription and its abnormal regulation was implicated in various aspects of cancer. However, the comprehensive understanding of HDACs and HATs in cancer is still lacking. Systematically analysis through 33 cancer types based on next-generation sequence data reveals heterogeneous expression pattern of HDACs and HATs across different cancer types. In particular, HDAC10 and HDAC6 show significant downregulation in most cancers. Principal components analysis (PCA) of pan-cancer reveals significant difference of HDACs and HATs between normal tissues and normal tissue adjacent to the tumor. The abnormal expression of HDACs and HATs was partially due to CNV and DNA methylation in multiple types of cancer. Prognostic significance (AUC reached 0.736) of HDACs and HATs demonstrates a five-gene signature including KAT2A, HAT1, KAT5, CREBBP and SIRT1 in KIRC. Analysis of NCI-60 drug database reveals the cytotoxic effect of several drugs are associated with dysregulated expression of HDACs and HATs. Analysis of immune infiltration and immunotherapy reveals that KAT2B and HDAC9 are associated with immune infiltration and immunotherapy. Our analysis provided comprehensive understanding of the regulation and implication of HDACs and HATs in pan-cancer. These findings provide novel evidence for biological investigating potential individual HDACs and HATs in the development and therapy of cancer in the future.

Genetic profile of Chinese patients with small bowel cancer categorized by anatomic location

BACKGROUND

Small bowel cancer (SBC) is a very rare solid malignancy. Consequently, compared with other malignant gastrointestinal tumors, our knowledge regarding SBC, specifically its molecular attributes, remains limited. Herein, we aim to provide an overview of the gene characteristics of Chinese patients with SBC, We particularly focus on elucidating the genetic intricacies that differentiate SBC patients whose primary tumors originate in distinct anatomical regions within the small bowel.

METHODS

During the period ranging from February 2018 to December 2022, a total of 298 tumor samples were consecutively collected from Chinese patients diagnosed with small bowel cancer.. Next-generation sequencing (NGS) was performed to detect gene mutation, assess microsatellite instability (MSI), and evaluate tumor mutational burden (TMB). Additionally,, IHC was used to analyze the level of PD-L1 expression within the samples.

RESULTS

The outcomes of the next-generation sequencing (NGS) unveiled the predominant gene mutations observed in Chinese patients with small bowel cancer (SBC). The top ten gene mutations identified were as follows: TP53 (53%), KRAS (51%), APC (31%), SMAD4 (19%), VEGFA (15%), CDKN2A (15%), RAC1 (15%), LRP1B (14%), MGMT (14%, CD74 (13%). Subsequent analysis revealed disparities in the gene landscape between the cohort in this study and that of the Memorial Sloan Kettering Cancer Center (MSKCC), Notably, distinguishable mutational frequencies were identified in several genes, including ERBB2, FBXW7, PIK3CA, etc. which exhibited contrasting presence in both this cohort and the MSKCC cohort.. Furthermore, we noticed variations in the frequency of gene mutations among SBC patients depending on the specific anatomical site where the tumors originated within the small bowel. In addition, the distribution of patients with high microsatellite instability (MSI-H) and tumor mutational burden (TMB) levels varied among SBC patients with tumors originating from the duodenum, jejunum, and ileum.

CONCLUSION

Chinese patients with small bowel cancer exhibited a distinct genetic profile in comparison to other populations, highlighting a unique genetic landscape. Furthermore, noticeable disparities in the genetic landscape were observed between patients with cancer situated in the duodenum and those with cancer affecting other regions of the small bowel, this suggests that these patients should be treated differently.

Proteomic Profiling and Tumor Microenvironment Characterization Reveal Molecular and Immunological Hallmarks of Left-Sided and Right-Sided Colon Cancer Tumorigenesis

Left-sided and right-sided colon cancer (LSCC and RSCC) display different biological and clinical characteristics. However, the differences in their tumorigenesis and tumor microenvironment remain unclear. In this study, we profiled the proteomic landscapes of LSCC and RSCC with data-independent acquisition mass spectrometry (DIA-MS) using fresh tumor and adjacent normal tissues from 24 patients. A total of 7403 proteingroups were primarily identified with DIA-MS. After quality control, 7212 proteingroups were used for further analysis. Through comparing the difference in proteomic profiles between LSCC and RSCC samples, 2556 commonly and 1982 region-type-specific regulated proteingroups were characterized. During the development of LSCC and RSCC, metabolic, growth, cell division, cell adhesion, and migration pathways were found to be significantly dysregulated (P < 0.05), which was further confirmed by transcriptome data from TCGA. Compared to RSCC, most parts of the immune-related signatures, immune cell infiltration scores, and overall immune scores of LSCC were higher. The systematic elucidation of proteomic and transcriptomic profiles in this work improves our understanding of tumorigenesis and immune microenvironment characteristics of LSCC and RSCC.

CXCR4 Expressed by Tumor-Infiltrating B Cells in Gastric Cancer Related to Survival in the Tumor Microenvironment: An Analysis Combining Single-Cell RNA Sequencing with Bulk RNA Sequencing

According to the World Health Organization (WHO), gastric cancer (GC) is the fourth leading cause of tumor-related mortality globally and one of the most prevalent malignant tumors. To better understand the role of tumor-infiltrating B cells (TIBs) in GC, this work used single-cell RNA sequencing (scRNA-Seq) and bulk RNA sequencing (bulk RNA-Seq) data to identify candidate hub genes. Both scRNA-Seq and bulk RNA-Seq data for stomach adenocarcinoma (STAD) were obtained from the GEO and TCGA databases, respectively. Using scRNA-seq data, the FindNeighbors and FindClusters tools were used to group the cells into distinct groups. Immune cell clusters were sought in the massive RNA-seq expression matrix using the single-sample gene set enrichment analysis (ssGSEA). The expression profiles were used in Weighted Gene Coexpression Network Analysis (WGCNA) to build TCGA's gene coexpression networks. Next, univariate Cox regression, LASSO regression, and Kaplan-Meier analyses were used to identify hub genes in scRNA-seq data from sequential B-cell analyses. Finally, we examined the correlation between the hub genes and TIBs utilizing the TISIDB database. We confirmed the immune-related markers in clinical validation samples using reverse transcriptase polymerase chain reaction (RT-PCR) and immunohistochemistry (IHC). 15 cell clusters were classified in the scRNA-seq database. According to the WGCNA findings, the green module is most associated with cancer and B cells. The intersection of 12 genes in two separate datasets (scRNA and bulk) was attained for further analysis. However, survival studies revealed that increased C-X-C motif chemokine receptor 4 (CXCR4) expression was linked to worse overall survival. CXCR4 expression is correlated with active, immature, and memory B cells in STAD were identified. Finally, RT-PCR and IHC assays verified that in GC, CXCR4 is overexpressed, and its expression level correlates with TIBs. We used scRNA-Seq and bulk RNA-Seq to study STAD's cellular composition. We found that CXCR4 is highly expressed by TIBs in GC, suggesting that it may serve as a hub gene for these cells and a starting point for future research into the molecular mechanisms by which these immune cells gain access to tumors and potentially identify therapeutic targets.

Comparative analyses of the prognosis, tumor immune microenvironment, and drug treatment response between left-sided and right-sided colon cancer by integrating scRNA-seq and bulk RNA-seq data

BACKGROUND

In this study, we compared the prognosis, tumor immune microenvironment (TIM), and drug treatment response between left-sided (LCC) and right-sided (RCC) colon cancer to predict outcomes in patients with LCC and RCC.

METHODS

Based on identified differentially expressed genes and using single-cell RNA sequencing data, we constructed and validated a prognostic model for LCC and RCC patients in the TCGA-COAD cohort and GSE103479 cohort. Moreover, we compared the differences of TIM characteristics and drug treatment response between LCC and RCC patients.

RESULTS

We constructed and validated a five-gene prognostic model for LCC patients and a four-gene prognostic model for RCC patients, and both showed excellent performance. The RCC patients with higher risk scores were significantly associated with greater metastasis (P = 2.6×10-5), N stage (P = 0.012), advanced pathological stage (P = 1.4×10-4), and more stable microsatellite status (P = 0.007) but not T stage (P = 0.200). For LCC patients, the risk scores were not significantly associated with tumor stage and microsatellite status (P > 0.05). Additionally, immune infiltration by CD8 and regulatory T cells and M0, M1, and M2 macrophages differed significantly between LCC and RCC patients (P < 0.05). APC and TP53 mutations were significantly more common in LCC patients (P < 0.05). In contrast, KRAS, SYNE1, and MUC16 mutations were significantly more common in RCC patients (P < 0.05). In addition, tumor mutation burden values were significantly higher in RCC patients than in LCC patients (P = 5.9×10-8). Moreover, the expression of immune checkpoint targets was significantly higher in RCC patients than in LCC patients (P < 0.05), indicating that RCC patients maybe more sensitive to immunotherapy. However, LCC and RCC patients did not differ significantly in their sensitivity to eight selected chemicals or target drugs (P > 0.05). The average half-maximal inhibitory concentrations for camptothecin, teniposide, vinorelbine, and mitoxantrone were significantly lower in low-risk than in high-risk RCC patients (P < 0.05), indicating that the lower risk score of RCC patients, the more sensitive they were to these four drugs.

CONCLUSIONS

We investigated the differences in prognosis, TIM, and drug treatment response between LCC and RCC patients, which may contribute to accurate colon cancer prognosis and treatment of colon cancer.

CHSY3 promotes proliferation and migration in gastric cancer and is associated with immune infiltration

BACKGROUND

The glycosyltransferase CHSY3 is a CHSY family member, yet its importance in the context of gastric cancer development remains incompletely understood. The present study was thus developed to explore the mechanistic importance of CHSY3 as a regulator of gastric cancer.

METHODS

Expression of CHSY3 was verified by TCGA, GEO and HPA databases. Kaplan-Meier curve, ROC, univariate cox, multivariate cox, and nomogram models were used to verify the prognostic impact and predictive value of CHSY3. KEGG and GO methods were used to identify signaling pathways associated with CHSY3. TIDE and IPS scores were used to assess the immunotherapeutic value of CHSY3. WGCNA, Cytoscape constructs PPI networks and random forest models to identify key Hub genes. Finally, qRT-PCR and immunohistochemical staining were performed to verify CHSY3 expression in clinical specimens. The ability of CHSY3 to regulate tumor was further assessed by CCK-8 assay and cloning assay, EDU assay, migration assay, invasion assay, and xenograft tumor model analysis.

RESULTS

The expression of CHSY3 was discovered to be abnormally upregulated in GC tissues through TCGA, GEO, and HPA databases, and the expression of CHSY3 was associated with poor prognosis in GC patients. Correlation analysis and Cox regression analysis revealed higher CHSY3 expression in higher T staging, an independent prognostic factor for GC. Moreover, elevated expression of CHSY3 was found to reduce the benefit of immunotherapy as assessed by the TIDE score and IPS score. Then, utilizing WGCNA, the PPI network constructed by Cytoscape, and random forest model, the Hub genes of COL5A2, POSTN, COL1A1, and FN1 associated with immunity were screened. Finally, the expression of CHSY3 in GC tissues was verified by qRT-PCR and immunohistochemical staining. Moreover, the expression of CHSY3 was further demonstrated by in vivo and in vitro experiments to promote the proliferation, migration, and invasive ability of GC.

CONCLUSIONS

The results of this study suggest that CHSY3 is an important regulator of gastric cancer progression, highlighting its promise as a therapeutic target for gastric cancer.

Construction of molecular typing in LIHC microenvironment based on lipid metabolism-related genes

Consensus on the stage of liver hepatocellular carcinoma (LIHC) in patients is difficult, which restricts the diagnosis and treatment of liver cancer. Molecular typing based on genes related to the lipid metabolism pathways can reflect deeper characteristics of liver cancer and complement the deficiency of the clinical staging system. In this study, we constructed and verified two cell subtypes: C1 and C2 in LIHC, based on six lipid metabolic pathway-associated genes identified in two independent external validation cohorts comprising single-cell RNA-sequencing technology (scRNA-Seq) data and bulk RNA-seq data downloaded from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The C2 subtype showed poorer prognosis, higher immune scores, and greater correlation with pathways associated with tumor progression as compared to the C1 subtype. Moreover, the sensitivity of many tested targeted drugs in C1 was relative to C2. Furthermore, Gene Set Enrichment Analysis (GSEA) revealed several significantly enriched oncological signatures and metabolic processes, which might help elucidate the underlying molecular mechanisms. At the same time, we identified there were significantly different metabolites in C1 and C2 subtypes using 11 LIHC tissue samples. In conclusion, we constructed two molecular subtypes based on the lipid metabolism-associated genes, which may provide valuable information to further study the pathogenesis and devise clinical management strategies for LIHC.

Inhibition of neuroactive ligand-receptor interaction pathway can enhance immunotherapy response in colon cancer: an in silico study

BACKGROUND

The potential mechanism underlying the association between Homologous recombination deficiency (HRD) and immunotherapy in colon cancer has not been investigated.

METHODS

The exon sequencing data and transcriptome data of 456 colon adenocarcinoma (COAD) patients were obtained from the TCGA database. Pathway activity score was calculated by GSVA methods and engaged in further survival analysis. The prognostic value of the candidate pathways was validated in an external GEO cohort and an immunotherapy cohort.

RESULTS

Patients with high HRD were associated with poor prognosis, lower tumor mutation burden and microsatellite instability, higher fraction genome alteration, and less sensitivity to immunotherapy in COAD. And then, the neuroactive ligand-receptor interaction pathway was over-activated in high-HRD tumors and associated with immunosuppression in colon cancer with high HRD. Besides, the pathway was associated with prognosis and immunotherapy response in COAD. Moreover, genes in this pathway such as LTB4R2 can be used as a novel target for therapy development in colon cancer.

CONCLUSION

Our study not only revealed the potential mechanism of HRD and the function of the neuroactive ligand-receptor interaction pathway in colon cancer but also provided new clues for the improvement of immunotherapy response in colon cancer.

Heterogeneity of cancer-associated fibroblasts in head and neck squamous cell carcinoma

Cancer-associated fibroblasts (CAFs) consist of heterogeneous cellular populations that contribute critical roles in head and neck squamous cell carcinoma (HNSCC). A series of computer-aided analyses were performed to determine various aspects of CAFs in HNSCC, including their cellular heterogeneity, prognostic value, relationship with immune suppression and immunotherapeutic response, intercellular communication, and metabolic activity. The prognostic significance of CKS2+ CAFs was verified using immunohistochemistry. Our findings revealed that fibroblasts group demonstrated prognostic significance, with the CKS2+ subset of inflammatory CAFs (iCAFs) exhibiting a significant correlation with unfavorable prognosis and being localized in close proximity to cancer cells. Patients with a high infiltration of CKS2+ CAFs had a poor overall survival rate. There is a negative correlation between CKS2+ iCAFs and cytotoxic CD8+ T cells and natural killer (NK) cells, while a positive correlation was found with exhausted CD8+ T cells. Additionally, patients in Cluster 3, characterized by a high proportion of CKS2+ iCAFs, and patients in Cluster 2, characterized by a high proportion of CKS2- iCAFs and CENPF-/MYLPF- myofibroblastic CAFs (myCAFs), did not exhibit significant immunotherapeutic responses. Moreover, close interactions was confirmed to exist between cancer cells and CKS2+ iCAFs/ CENPF+ myCAFs. Furthermore, CKS2+ iCAFs demonstrated the highest level of metabolic activity. In summary, our study enhances the understanding of the heterogeneity of CAFs and provided insights into improving the efficacy of immunotherapies and prognostic accuracy for HNSCC patients.

Construction of a novel immune response prediction signature to predict the efficacy of immune checkpoint inhibitors in clear cell renal cell carcinoma patients

Background

Immune checkpoint inhibitor (ICI) treatment has enhanced survival outcomes in clear cell renal cell carcinoma (ccRCC) patients. Nevertheless, the effectiveness of immunotherapy in ccRCC patients is restricted and we intended to develop and characterize an immune response prediction signature (IRPS) to forecast the efficacy of immunotherapy.

Methods

RNA-seq expression profile and clinicopathologic characteristics of 539 kidney cancer and 72 patients with normal specimens, were downloaded from the Cancer Genome Atlas (TCGA) database, while the Gene Expression Omnibus (GEO) database was used as the validation set, which included 24 ccRCC samples. Utilization of the TCGA data and immune genes databases (ImmPort and the InnateDB), we explored through Weighted Gene Co-expression Network Analysis (WGCNA), along with Least Absolute Shrinkage and Selection Operator method (LASSO), and constructed an IRPS for kidney cancer patients. GSEA and CIBERSORT were performed to declare the molecular and immunologic mechanism underlying the predictive value of IRPS. The Human Protein Atlas (HPA) was deployed to verify the protein expressions of IRPS genes. Tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS) were computed to determine the risk of immune escape and value the discrimination of IRPS. A ccRCC cohort with anti-PD-1 therapy was obtained as an external validation data set to verify the predictive value of IRPS.

Results

We constructed a 10 gene signature related to the prognosis and immune response of ccRCC patients. Considering the IRPS risk score, patients were split into high and low risk groups. Patients with high risk in the TCGA cohort tended towards advanced tumor stage and grade with poor prognosis (p < 0.001), which was validated in GEO database (p = 0.004). High-risk group tumors were related with lower PD-L1 expression, higher TMB, higher MSIsensor score, lower IPS, higher TIDE score, and enriched Treg cells, which might be the potential mechanism of immune dysfunction and exclusion. Patients in the IRPS low risk group had better PFS (HR:0.73; 95% CI: 0.54-1.0; P = 0.047).

Conclusion

A novel biomarker of IRPS was constructed to predict the benefit of immunotherapy, which might lead to more individualized prognoses and tailored therapy for kidney cancer patients.

Correlation analysis of PBX family with immune invasion and drug sensitivity in colon adenocarcinoma

Objedtive

Pre-B cell leukemia (PBX) has been found to be associated with cancer, but poorly studied with colon adenocarcinoma (COAD). In this study, the correlation between PBX family and COAD pathogenesis and immune cytokine infiltration was further explored by analyzing online tumor databases, in order to find new biomarkers for the diagnosis of COAD.

Methods

The online database was used to analyze gene differential expression, methylation level, gene mutation rate, immune infiltration difference, drug sensitivity, and so on.

Results

PBX1 and PBX3 decreased in COAD. PBX2 and PBX4 increased. The expression of PBX1 and PBX2 in different clinical stages was different. PBX4 was valuable for the prognosis of COAD. PBX family has correlation between COAD and immune infiltration. PBX2 was correlated with different pathological stages. PBX3 had the highest gene mutation rate, followed by PBX1, PBX2 and PBX4. PBX1, PBX2 and PBX4 were correlated with the sensitivity of multiple drugs.

Conclusion

The PBX family is differentially expressed in COAD and has a genetic mutation, and its protein network is closely related to the HOX family and is associated with immune infiltration of COAD.

Classification of the mitochondrial ribosomal protein-associated molecular subtypes and identified a serological diagnostic biomarker in hepatocellular carcinoma

Purpose

The objective of this study was to sort out innovative molecular subtypes associated with mitochondrial ribosomal proteins (MRPs) to predict clinical therapy response and determine the presence of circulating markers in hepatocellular carcinoma (HCC) patients.

Methods

Using an unsupervised clustering method, we categorized the relative molecular subtypes of MRPs in HCC patients. The prognosis, biological properties, immune checkpoint inhibitor and chemotherapy response of the patients were clarified. A signature and nomogram were developed to evaluate the prognosis. Enzyme-linked immunosorbent assay (ELISA) measured serum mitochondrial ribosomal protein L9 (MRPL9) levels in liver disease patients and normal individuals. Receiver operating characteristic (ROC) curves were conducted to calculate the diagnostic effect. The Cell Counting Kit 8 was carried out to examine cell proliferation, and flow cytometry was used to investigate the cell cycle. Transwell assay was applied to investigate the potential of cell migration and invasion. Western blot detected corresponding changes of biological markers.

Results

Participants were classified into two subtypes according to MRPs expression levels, which were characterized by different prognoses, biological features, and marked differences in response to chemotherapy and immune checkpoint inhibitors. Serum MRPL9 was significantly higher in HCC patients than in normal individuals and the benign liver disease group. ROC curve analysis showed that MRPL9 was superior to AFP and Ferritin in differentiating HCC from healthy and benign patients, or alone. Overexpressed MRPL9 could enhance aggressiveness and facilitate the G1/S progression in HCC cells.

Conclusion

We constructed novel molecular subtypes based on MRPs expression in HCC patients, which provided valuable strategies for the prediction of prognosis and clinical personalized treatment. MRPL9 might act as a reliable circulating diagnostic biomarker and therapeutic target for HCC patients.

Identification of a tissue resident memory CD8 T cell-related risk score signature for colorectal cancer, the association with TME landscapes and therapeutic responses

Backgrounds: The tissue resident memory CD8 T cell (Trm) constitutes an important component of the local immunity. In the context of malignant tumors, mounting evidence also supports the potential anti-tumor property of this cell subset. Therefore, identification of Trm marker genes and exploration of the causative effect of Trm in shaping tumor microenvironment (TME) heterogeneity might provide novel insights for the comprehensive management of cancer patients. Methods: By dissecting a single T cell transcriptome dataset, we acquired marker genes for Trm, which were latter applied to bulk RNA sequencing profiles of two large colorectal cancer (CRC) patient cohorts downloaded from TCGA and GEO databases. First, colorectal cancer patients were divided into different Trm clusters using consensus clustering algorithm. Then, we established a Trm-related gene (TRMRG) risk score signature and tested its efficacy in predicting prognosis for colorectal cancer patients. Moreover, a sequence of rigorous and robust analyses were also carried out to investigate the potential role of Trm-related gene risk score in tumor microenvironment remodeling and therapeutic utility of it in colorectal cancer treatment. Results: A total of 49 Trm marker genes were identified by analyzing single cell RNA sequencing profiles. First, colorectal cancer patients were successfully classified into two Trm clusters with significant heterogeneity in functional enrichment patterns and tumor microenvironment landscapes. Then, we developed a Trm-related gene risk score signature and divided patients into different risk levels. High risk patients were characterized by attenuated immunogenicity, weakened sensitivity to immunotherapy, as well as adverse clinical outcomes. While low risk patients with advantages in survival exhibited increased immunogenicity, stronger metabolic activity and improved immunotherapeutic responses. Conclusion: Through combinatorial analysis of single cell and bulk RNA sequencing data, the present study identified Trm to play a non-negligible role in regulating the complexity and heterogeneity of tumor microenvironment for colorectal cancer. Moreover, the Trm-related gene risk score signature developed currently was corroborated to be tightly correlated with prognosis and therapeutic responses of colorectal cancer patients, thus exhibiting potential application value for clinical practice.

Exploring biomarkers for prognosis and neoadjuvant chemosensitivity in rectal cancer: Multi-omics and ctDNA sequencing collaboration

Introduction

This study aimed to identified the key genes and sequencing metrics for predicting prognosis and efficacy of neoadjuvant chemotherapy (nCT) in rectal cancer (RC) based on genomic DNA sequencing in samples with different origin and multi-omics association database.

Methods

We collected 16 RC patients and obtained DNA sequencing data from cancer tissues and plasma cell-free DNA before and after nCT. Various gene variations were analyzed, including single nucleotide variants (SNV), copy number variation (CNV), tumor mutation burden (TMB), copy number instability (CNI) and mutant-allele tumor heterogeneity (MATH). We also identified genes by which CNV level can differentiate the response to nCT. The Cancer Genome Atlas database and the Clinical Proteomic Tumor Analysis Consortium database were used to further evaluate the specific role of therapeutic relevant genes and screen out the key genes in multi-omics levels. After the intersection of the screened genes from differential expression analysis, survival analysis and principal components analysis dimensionality reduction cluster analysis, the key genes were finally identified.

Results

The genes CNV level of principal component genes in baseline blood and cancer tissues could significantly distinguish the two groups of patients. The CNV of HSP90AA1, EGFR, SRC, MTOR, etc. were relatively gained in the better group compared with the poor group in baseline blood. The CNI and TMB was significantly different between the two groups. The increased expression of HSP90AA1, EGFR, and SRC was associated with increased sensitivity to multiple chemotherapeutic drugs. The nCT predictive score obtained by therapeutic relevant genes could be a potential prognostic indicator, and the combination with TMB could further refine prognostic prediction for patients. After a series of analysis in multi-omics association database, EGFR and HSP90AA1 with significant differences in multiple aspects were identified as the key predictive genes related to prognosis and the sensitivity of nCT.

Discussion

This work revealed that effective combined application and analysis in multi-omics data are critical to search for predictive biomarkers. The key genes EGFR and HSP90AA1 could serve as an effective biomarker to predict prognose and neoadjuvant chemosensitivity.

Characterizing the molecular heterogeneity of clear cell renal cell carcinoma subgroups classified by miRNA expression profile

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous disease that is associated with poor prognosis. Recent works have revealed the significant roles of miRNA in ccRCC initiation and progression. Comprehensive characterization of ccRCC based on the prognostic miRNAs would contribute to clinicians’ early detection and targeted treatment. Here, we performed unsupervised clustering using TCGA-retrieved prognostic miRNAs expression profiles. Two ccRCC subtypes were identified after assessing principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and consensus heatmaps. We found that the two subtypes are associated with distinct clinical features, overall survivals, and molecular characteristics. C1 cluster enriched patients in relatively early stage and have better prognosis while patients in C2 cluster have poor prognosis with relatively advanced state. Mechanistically, we found the differentially expressed genes (DEGs) between the indicated subgroups dominantly enriched in biological processes related to transmembrane transport activity. In addition, we also revealed a miRNA-centered DEGs regulatory network, which severed as essential regulators in both transmembrane transport activity control and ccRCC progression. Together, our work described the molecular heterogeneity among ccRCC cancers, provided potential targets served as effective biomarkers for ccRCC diagnosis and prognosis, and paved avenues to better understand miRNA-directed regulatory network in ccRCC progression.

Deciphering colorectal cancer immune microenvironment transcriptional landscape on single cell resolution – A role for immunotherapy

Single cell RNA sequencing (scRNA-seq) is a novel high-throughput technique that enables the investigation of a single cell’s entire transcriptome. It elucidates intricate cellular networks and generates indices that will eventually enable the development of more targeted and personalized medications. The importance of scRNA-seq has been highlighted in complex biological systems such as cancer and the immune system, which exhibit significant cellular heterogeneity. Colorectal cancer (CRC) is the third most common type of cancer and the second leading cause of cancer-related death globally. Chemotherapy continues to be used to treat these patients. However, 5-FU has been utilized in chemotherapy regimens with oxaliplatin and irinotecan since the 1960s and is still used today. Additionally, chemotherapy-resistant metastatic CRCs with poor prognoses have been treated with immunotherapy employing monoclonal antibodies, immune checkpoint inhibitors, adoptive cell therapy and cancer vaccines. Personalized immunotherapy employing tumor-specific neoantigens allows for treating each patient as a distinct group. Sequencing and multi-omics approaches have helped us identify patients more precisely in the last decade. The introduction of modern methods and neoantigen-based immunotherapy may usher in a new era in treating CRC. The unmet goal is to better understand the cellular and molecular mechanisms that contribute to CRC pathogenesis and resistance to treatment, identify novel therapeutic targets, and make more stratified and informed treatment decisions using single cell approaches. This review summarizes current scRNA-seq utilization in CRC research, examining its potential utility in the development of precision immunotherapy for CRC.

Identification of a novel cellular senescence-related signature for the prediction of prognosis and immunotherapy response in colon cancer

The study was conducted to construct a cellular senescence-related risk score signature to predict prognosis and immunotherapy response in colon cancer. Colon cancer data were acquired from the Gene Expression Omnibus and The Cancer Genome Atlas databases. And cellular senescence-related genes were obtained from the CellAge database. The colon cancer data were classified into different clusters based on cellular senescence-related gene expression. Next, prognostic differential genes among clusters were identified with survival analysis. A cellular senescence-related risk score signature was developed by performing the LASSO regression analysis. Finally, PCA analysis, t-SNE analysis, Kaplan-Meier survival analysis, ROC analysis, univariate Cox regression analysis, multivariate Cox regression analysis, C-index analysis, meta-analysis, immune infiltration analysis, and IPS score analysis were used to evaluate the significance of the risk signature for predicting prognosis and immunotherapy response in colon cancer. The colon cancer data were classified into three clusters. The patients in cluster A and cluster B had longer survival. A cellular senescence-related risk score signature was developed. Patients in the low-risk score group showed a better prognosis. The risk score signature could predict colon cancer patients’ prognosis independently of other clinical characteristics. The risk score signature predicted the prognosis of colon cancer patients more accurately than other signatures. Patients in the low-risk score group showed a better response to immunotherapy. The opposite was true for the high-risk score group. In conclusion, the cellular senescence-related risk score signature could be used for the prediction of prognosis and immunotherapy response in colon cancer.

Construction of immunotherapy-related prognostic gene signature and small molecule drug prediction for cutaneous melanoma

Background

Cutaneous melanoma (CM), a kind of skin cancer with a high rate of advanced mortality, exhibits a wide variety of driver and transmitter gene alterations in the immunological tumor microenvironment (TME) associated with tumor cell survival and proliferation.

Methods

We analyzed the immunological infiltration of TME cells in normal and malignant tissues using 469 CM and 556 normal skin samples. We used a single sample gene set enrichment assay (ssGSEA) to quantify the relative abundance of 28 cells, then used the LASSO COX regression model to develop a riskScore prognostic model, followed by a small molecule drug screening and molecular docking validation, which was then validated using qRT-PCR and IHC.

Results

We developed a prognosis model around seven essential protective genes for the first time, dramatically elevated in tumor tissues, as did immune cell infiltration. Multivariate Cox regression results indicated that riskScore is an independent and robust prognostic indicator, and its predictive value in immunotherapy was verified. Additionally, we identified Gabapentin as a possible small molecule therapeutic for CM.

Conclusions

A riskScore model was developed in this work to analyze patient prognosis, TME cell infiltration features, and treatment responsiveness. The development of this model not only aids in predicting patient response to immunotherapy but also has significant implications for the development of novel immunotherapeutic agents and the promotion of tailored treatment regimens.

The Multi-Omics Landscape and Clinical Relevance of the Immunological Signature of Phagocytosis Regulators: Implications for Risk Classification and Frontline Therapies in Skin Cutaneous Melanoma

Simple Summary

In this study, we focused on exploring phagocytosis regulators’ expression and mutational characteristics in skin cutaneous melanoma samples and delineating two molecular subtypes based on expression characteristics. We determined the relationship between phagocytosis regulators and survival by survival analysis of molecular subtypes. We then constructed a survival model (PRRS) to further quantify the criteria. Moreover, we combined pathway analysis, immune infiltration analysis, and mutation analysis to deeply explore the effects of phagocytosis regulators on skin cutaneous melanoma samples.

Abstract

Tumor-associated macrophages (TAMs) have gained considerable attention as therapeutic targets. Monoclonal antibody treatments directed against tumor antigens contribute significantly to cancer cell clearance by activating macrophages to phagocytose tumor cells. Due to its complicated genetic and molecular pathways, skin cutaneous melanoma (SKCM) has not yet attained the expected clinical efficacy and prognosis when compared to other skin cancers. Therefore, we chose TAMs as an entrance point. This study aimed to thoroughly assess the dysregulation and regulatory role of phagocytosis regulators in SKCM, as well as to understand their regulatory patterns in SKCM. This study subtyped prognosis-related phagocytosis regulators to investigate prognostic differences between subtypes. Then, we screened prognostic factors and constructed phagocytosis-related scoring models for survival prediction using differentially expressed genes (DEGs) between subtypes. Additionally, we investigated alternative treatment options using chemotherapeutic drug response data and clinical cohort treatment data. We first characterized and generalized phagocytosis regulators in SKCM and extensively examined the tumor immune cell infiltration. We created two phagocytosis regulator-related system (PRRS) phenotypes and derived PRRS scores using a principal component analysis (PCA) technique. We discovered that subtypes with low PRRS scores had a poor prognosis and decreased immune checkpoint-associated gene expression levels. We observed significant therapeutic and clinical improvements in patients with higher PRRS scores. Our findings imply that the PRRS scoring system can be employed as an independent and robust prognostic biomarker, serving as a critical reference point for developing novel immunotherapeutic methods.

Necroptosis-Related Genes Associated With Immune Activity and Prognosis of Colorectal Cancer

This study aims at screening out the key necroptosis-related genes in colorectal cancer and elucidating the role of necroptosis-related genes in the immune activity and prognosis of colorectal cancer (CRC). The CRC patients’ data were downloaded from The Cancer Genome Atlas (TCGA). The non-negative matrix factorization method was applied to identify new molecular subgroups. Survival analysis and single sample Gene Set Enrichment Analysis were performed to determinate the differences in the overall survival time and immune status of the subgroups. Prognostic model was constructed on the basis of univariate Cox regression and LASSO analysis. Functional analyses were used to explore the potential mechanisms. Based on prognostic related necroptosis genes, we identify two molecular subgroups with significantly different survival. The better prognosis was associated with more active immune infiltration and upregulated expression of immune checkpoints. We screened nine necroptosis related genes as key prognostic genes and established a risk model, which showed a good potential for survival prediction in colorectal cancer. Nomogram assessment showed that the model had high reliability for predicting the prognosis of colorectal cancer patients. The high-risk and low-risk group also has different sensitivity to immunotherapy and commonly used drugs for colorectal cancer. Overall, necroptosis related genes were involved in the immune microenvironment of colorectal cancer patient, could be utilized to predict the prognosis of colorectal cancer and develop more individualized treatment.

Prognosis and Immunotherapy Response With a Novel Golgi Apparatus Signature-Based Formula in Lung Adenocarcinoma

The Golgi apparatus (GA) is a cellular organelle that participates in the packaging, modification, and transport of proteins and lipids from the endoplasmic reticulum to be further fabricated before being presented to other cellular components. Recent studies have demonstrated that GA facilitates numerous cellular processes in cancer development. Therefore, this study aimed to establish a novel lung adenocarcinoma (LUAD) risk evaluation model based on GA gene signatures. In this study, we used TCGA-LUAD (n = 500) as the training cohort and GSE50081 (n = 127), GSE68465 (442), and GSE72094 (398) as the validation cohorts. Two immunotherapy datasets (GSE135222 and GSE126044) were also obtained from a previous study. Based on machine algorithms and bioinformatics methods, a GA gene-related risk score (GARS) was established. We found that the GARS independently predicted the prognosis of LUAD patients and remained effective across stages IA to IIIA. Then, we identified that the GARS was highly correlated with mutations in P53 and TTN. Further, this study identified that GARS is related to multiple immune microenvironmental characteristics. Furthermore, we investigated GSE135222 and GSE126044 and found that a lower GARS may be indicative of an improved therapeutic effect of PD-1/PD-L1 therapy. We also found that high GARS may lead to a better response to multiple anticancer drugs. Finally, we established a nomogram to better guide clinical application. To our knowledge, this is the first study to demonstrate a novel GA signature-based risk score formula to predict clinical prognosis and guide the treatment of LUAD patients.