Spatial analysis of tumor-infiltrating lymphocytes in histological sections using deep learning techniques predicts survival in colorectal carcinoma.

Objective In this study, our goal was to explore the role of metabolism-associated genes in colorectal cancer (CRC) and construct a prognostic model for patients with CRC. Methods Differential expression analysis was conducted using RNA-sequencing data from The Cancer Genome Atlas (TCGA) dataset. Enrichment analyses were performed to determine the function of dysregulated metabolism-associated genes. The protein-protein interaction (PPI) network, Kaplan-Meier curves, and stepwise Cox regression analyses identified key metabolism-associated genes. A prognostic model was constructed using LASSO Cox regression analysis and visualized as a nomogram. Survival analyses were conducted in the TCGA and Expression Omnibus (GEO) cohorts to demonstrate the predictive ability of the model. Results A total of 332 differentially expressed metabolism-associated genes in CRC were screened from the TCGA cohort. Differentially expressed metabolism-associated genes mainly participate in the metabolism of nucleoside phosphate, ribose phosphate, lipids, and fatty acids. A PPI network was constructed out of 328 key genes. A prognostic model was established based on five prognostic genes (ALAD, CHDH, ISYNA1, NAT1, and P4HA1) and was demonstrated to predict survival in the TCGA and GEO cohorts accurately. Conclusion The metabolism-associated prognostic model can predict the survival of patients with CRC. Our work supplements previous work focusing on determining prognostic factors of CRC and lays a foundation for further mechanistic exploration.

Introduction: There is evidence to suggest that the biology of breast cancer (BC) might vary according to age, as BCs in elderly patients might be associated with accumulation of DNA damage and BCs in younger individuals might be enriched for genetic alterations affecting cancer predisposition genes. Whether the genetic landscape of BC in elderly individuals differs is yet to be determined. Here, we sought to describe the spectrum of somatic genetic alterations and mutational signatures in BC according to age. Materials and Methods: We conducted a re-analysis of two cohorts of BC: i) MSK-IMPACT targeted sequencing cohort (primary, n=918; metastatic, n=1,000) and ii) whole-exome sequencing data of primary BCs from The Cancer Genome Atlas (TCGA) BC study (n=1087). BCs of younger (<65 years old) and elderly individuals (≥ 65 years old) were compared, matched by estrogen receptor (ER)/HER2 status at a 2:1 ratio (MSK-IMPACT) or a 1:1 ratio (TCGA). Somatic single nucleotide variants and copy number alterations (CNAs) were determined using a validated bioinformatics pipeline, and mutational signatures were defined using DeconstructSigs and SigMA. Two-tailed Fisher’s exact test was performed. Results: Primary BCs in elderly and younger patients, matched by ER/HER2 status, from the MSK-IMPACT (n=220 and n=440) and TCGA (n=290, each) cohorts, and metastatic BCs from elderly (n=98) and younger (n=196) patients from the MSK-IMPACT cohort, matched by ER/HER2 status, were compared. In both cohorts of primary BCs, PIK3CA, TP53 and CDH1 were the most frequently mutated genes. Compared to younger patients, primary BCs in elderly patients from the MSK-IMPACT cohort displayed a lower frequency of mutations in TP53 (23% vs 34%, P<0.01), AKT1 (2% vs 6%, P<0.05) and MAP2K4 (0.4% vs 4%, P<0.01). In the TCGA cohort, somatic mutations in AKT1 were found to be less frequent in elderly than in younger patients (1% vs 5%, P<0.05), whereas NF1 (2% vs 6%, P<0.05) mutations were more frequent in elderly than in younger patients with primary BCs. Our analyses of BC metastases subjected to MSK-IMPACT revealed that elderly patients harbored a higher frequency of mutations in NCOR1 (11% vs 4%, P<0.05) and RUNX1 (9% vs 2%, P<0.05) than younger patients. The frequency of bi-allelic inactivation of homologous recombination DNA repair deficiency (HRD) genes (i.e. BRCA1, BRCA2, PALB2, RAD51C and RAD51D) in primary BCs of elderly and younger individuals in the TCGA cohort was 2% and 5%, respectively. No differences in the frequency of CNAs were observed between the two groups. The most frequent mutational signatures found in primary BCs of elderly and younger patients were aging, APOBEC and HRD in the MSK-IMPACT cohort, and aging, APOBEC and HRD in primary BCs of the TCGA cohort, with APOBEC being enriched in younger patients compared to elderly patients. The most frequent mutational signatures in metastatic BCs in elderly and younger individuals of the MSK-IMPACT cohort were APOBEC followed by aging and HRD. Conclusion: Our findings show that BCs in elderly patients harbor a lower frequency of somatic mutations in TP53, AKT1 and MAP2K4 than younger individuals. In contrast, BCs in elderly patients more frequently harbor somatic mutations in the transcription factors RUNX1 and NCOR1. Bi-allelic alterations affecting HRD-related genes was numerically more frequent in younger than in older patients. As expected, BCs in elderly patients show a numerically higher incidence of the aging signature, whereas primary BCs affecting younger patients displayed a higher frequency of the APOBEC signature than primary BCs from elderly individuals. Citation Format: Pier Selenica, Fresia Pareja, Audree Tadros, Lorenzo Ferrando, David N Brown, Hong Zhang, Pedram Razavi, Diana Mandelker, Mark E Robson, Sarat Chandarlapaty, Britta Weigelt, Jorge S Reis-Filho. Genomic landscape of breast cancer occurring in elderly individuals [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-05-08.

Vascular endothelial growth factor-A (VEGFA) is a key inducer of angiogenesis, responsible for generating new blood vessels in the tumor microenvironment (TME) and facilitating metastasis. Notably, Avastin, which targets VEGFA, failed to demonstrate any significant benefit in clinical trials for breast cancer (BC). This study aimed to investigate the clinical relevance of VEGFA gene expression in BC. A total of 7,336 BC patients across eight independent cohorts: ISPY2 (GSE173839), Sweden Cancerome Analysis Network-Breast (SCAN-B) (GSE96058), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), GSE25066, GSE163882, GSE34138, GSE20194, and The Cancer Genome Atlas (TCGA), were analyzed. The calculated median VEGFA expression level was used to stratify these cohorts into high and low groups. High VEGFA was associated with worse disease-free, disease-specific, and overall survival in the METABRIC cohort, with findings supported by the SCAN-B cohort, which also showed worse overall survival (all P < 0.02). High VEGFA expression was seen in triple-negative breast cancer (TNBC) but not in BC with lymph node metastasis. Additionally, there was a significant correlation between high VEGFA expression and higher silent and non-silent mutations, single-nucleotide variant (SNV) neoantigens, homologous recombination defect, intratumoral heterogeneity, in the TCGA cohort. In the TCGA, METABRIC, and SCAN-B cohorts, high VEGFA BC was also associated with higher cell proliferation: higher Ki67 gene expression, higher Nottingham histological grade, and consistent enrichment of all the Hallmark cell proliferation-related gene sets. Unexpectedly, the angiogenesis gene set was not enriched in any of the cohorts and showed no association with infiltrations of lymphatic or blood vascular endothelial cells besides pericytes. High VEGFA BC had significantly less infiltration of anti-cancer immune cells but higher infiltration of pro-cancer immune cells in TCGA, METABRIC, and SCAN-B cohorts. Interestingly, BC, which had a pathological complete response (pCR) after anthracycline- and taxane-based neoadjuvant therapy, was associated with significantly heightened VEGFA expression in both estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)- and TNBC subtypes in the GSE25066 cohort and after immunotherapy in ER+/ HER2- subtype, but not TNBC in the ISPY2 cohort. Our research indicates that high VEGFA BC confers high cell proliferation, reduced immune cell infiltration, and poorer survival, but allows better response to anthracycline- and taxane-based chemotherapy, and immunotherapy.

CD3+ cells at the invasive margin of deeply invading (pT3–T4) colorectal cancer and risk of post-surgical metastasis: a longitudinal study

Purpose: We aimed to develop and validate a novel gene signature from published data and improve the prediction of survival in muscle-invasive bladder cancer (MIBC).Methods: We searched the published gene signatures associated with the overall survival (OS) of MIBC and compiled all 274 genes to develop a novel gene signature. RNAseq data of TCGA (the Cancer Genome Atlas) bladder cohort were downloaded. All genes were included in a univariate Cox hazard ratio model. We then used a reduced multivariate Cox regression model, which included only genes achieving P < 0.05 in the univariate model. A total of 172 patients at Fudan University Shanghai Cancer Center (FUSCC) and 61 patients from GEO datasets were used as an external validation set.Results: A total of 327 patients in the TCGA cohort were enrolled. We identified 274 genes from eight published papers on the OS of MIBC. Using the TCGA database, we identified 12 genes that correlated with OS (P < 0.05 in both univariate and multivariate analyses). By integrating these genes with the RT-qPCR data in our validation dataset and GEO datasets, we confirmed that the power for predicting OS of the 12-gene panel (AUC of 0.741 and 0.727, respectively) was higher than just clinical data (including gender, age, T stage, grade, and N stage) alone in the TCGA and FUSCC cohort (AUC of 0.667 and 0.631, respectively). Additionally, upon combining the clinical data and 12-gene panel together, the AUC increased to 0.768, 0.757, and 0.88 in the TCGA, FUSCC and GSE13507 cohorts, respectively.Conclusions: Applying published gene signatures and TCGA data, we successfully built and externally validated a novel 12-gene signature for the survival of MIBC.Brief ExplanationWe systemically reviewed all published prognostic gene signatures of muscle-invasive bladder cancer (MIBC) and integrated the genes in the TCGA MIBC cohort. This new gene panel was validated in a newly established MIBC cohort in GEO and FUSCC. This method can help update the previous established panels in a new way.

BackgroundNewer strategies of targeting HER2 such as novel HER2-targeted agents and combination with immune checkpoint inhibitors (ICIs) call for development of newer biomarkers based on deeper understanding of biology. To...

Background: The Breast Cancer Index (BCI) is an algorithmic gene expression-based signature comprised of two functional biomarker panels, the Molecular Grade Index (MGI) and the two-gene ratio, HOXB13/IL17BR. The HOXB13/IL17BR ratio has been shown to predict endocrine response across several different treatment scenarios, and the homeobox factor, HOXB13, is the primary determinant of endocrine benefit and response. Previously, we found that HOXB13 gene expression was positively correlated with HER2 in estrogen receptor-positive (ER+) but not ER-negative (ER-) tumors. To validate these findings, we examined HOXB13 gene expression in The Cancer Genome Atlas (TCGA) breast cancer cohort. In addition, considering that the HOXB13 gene locus resides 9 megabases from the HER2 locus at chromosome 17q21-22, we examined whether HOXB13 was coamplified with HER2 in HER2-positive breast cancers. Methods: Messenger RNA (mRNA) sequencing (mRNAseq) data from the TCGA breast cancer dataset were used to correlate HOXB13 gene expression with immunohistochemical (IHC)-based HER2 expression in ER+ (ER+PR+, ER+PR-) and ER- (ER-PR+ and ER-PR-) breast cancers. Thresholded copy number data from GISTIC output and mRNAseq data from the TCGA datasets were used to correlate HER2 and HOXB13 gene amplification (at least 4 inferred copies) with HOXB13 gene expression in IHC-based ER+ (n= 562) and ER- (n=163) breast cancer subsets. Formalin-fixed paraffin embedded (FFPE) samples from 80 consecutive HER2-amplified invasive breast carcinomas (64 ER+, 16 ER-) diagnosed between 2010 and 2013 were retrospectively collected from the MGH clinical archives and processed for fluorescence in situ hybridization (FISH) for HER2 (spectrum orange) HOXB13 (spectrum green) and CEP17 (spectrum blue). A ratio of &amp;gt; 2.0 HER2 and HOXB13 to CEP17 signals in at least 60 interphase tumor cell nuclei was considered as amplification of HER2 and HOXB13.Results: In the TCGA breast tumors, HOXB13 gene expression was significantly higher in HER2 positive (by IHC status) tumors in both ER+ (p= 3.7 x10-5) and ER- (p= 4.7 x10-4) tumors compared to HER2-negative samples. In HER2+ TCGA breast tumors, genomic analysis revealed co-amplification of HOXB13 with HER2 in 27% of all tumors, and 25.3% and 31.7% in the ER+ and ER- subsets, respectively. Amplification of the HOXB13 locus alone was observed in 2.4% of HER2-non amplified ER+ and ER- TCGA tumors. In the TCGA cohort, median HOXB13 gene expression was not significantly different when comparing HER2-amplified and HER2/HOXB13 coamplified ER+ (p= 0.33) and ER- (p=0.052) tumors, HER2-amplified and HER2-nonamplified ER+ (p=0.42) and ER- (p=0.67) tumors, and HER2/HOXB13 coamplified and HER2-nonamplified ER+ (p=0.50) and ER- (p=0.11) tumors. Lastly, in the consecutive case series of 80 HER2-amplified breast cancers from MGH, HOXB13 was coamplified in 23% of all tumors, and 23.4% and 18.75% in the ER+ and ER- subsets, respectively. Conclusion: HOXB13 was coamplified with HER2 in a substantial subset of TCGA and MGH primary breast cancers irrespective of ER status. Citation Format: Dennis Sgroi, Maristela Onozato, Irene Mitsiades, Ryan McMullin, Daniel Hicks, Angela Volorio, Esther Rheinbay. HOXB13 is coamplified with HER2 in a subset of breast cancers [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-08-03.

Growing evidence has indicated that prognostic biomarkers have a pivotal role in tumor and immunity biological processes. TP53 mutation can cause a range of changes in immune response, progression, and prognosis of colorectal cancer (CRC). Thus, we aim to build an immunoscore prognostic model that may enhance the prognosis of CRC from an immunological perspective. We estimated the proportion of immune cells in the GSE39582 public dataset using the CIBERSORT (Cell type identification by estimating relative subset of known RNA transcripts) algorithm. Prognostic genes that were used to establish the immunoscore model were generated by the LASSO (Least absolute shrinkage and selection operator) Cox regression model. We established and validated the immunoscore model in GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas) cohorts, respectively; significant differences of overall survival analysis were found between the low and high immunoscore groups or TP53 subgroups. In the multivariable Cox analysis, we observed that the immunoscore was an independent prognostic factor both in the GEO cohort (HR (Hazard ratio) 1.76, 95% CI (confidence intervals): 1.26–2.46) and the TCGA cohort (HR 1.95, 95% CI: 1.20–3.18). Furthermore, we established a nomogram for clinical application, and the results suggest that the nomogram is a better predictive model for prognosis than immunoscore or TNM staging.

ObjectiveThe current study aims to identify the dysregulated pathway involved in carcinogenesis and the essential survival-related dysregulated genes among this pathway in the early stage of lung adenocarcinoma (LUAD).Patients and MethodsData from The Cancer Genome Atlas (TCGA) including 526 tumor tissues of LUAD and 59 healthy lung tissues were analyzed to gain differentially expressed genes (DEGs). Gene ontology (GO) analysis was conducted with DAVID, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs was performed, followed by gene set enrichment analysis (GSEA) methods. Survival analysis was implemented in TCGA dataset and validated in Gene Expression Omnibus (GEO) cohort GSE50081, which includes 127 patients with stage I LUAD.ResultsGSEA enrichment analysis suggested that homologous recombination repair (HRR) pathway was significantly enriched. Subsequent KEGG pathway enrichment analysis indicated the significant up-regulation of HRR pathway in patients with T1 stage LUAD. Retrieved in Gene database, RAD54L is involved in HRR pathway and were recognized to be significantly differentially expressed in T1 stage LUAD in our study. The survival analysis indicated that high expression of RAD54L was significantly related to worse overall survival in patients with T1 stage LUAD (TCGA cohort: HR=2.10, 95% CI [1.47–2.98], P = 0.001; GSE50081 validation cohort: HR = 2.61, 95% CI [1.51–4.52], P = 0.002). Multivariate cox regression analysis indicated that RAD54L is an independent prognostic factor in the early-stage LUAD.ConclusionHRR pathway is up-regulated in LUAD, among which the expression of RAD54L was found to be significantly differentially expressed in T1 stage tumor tissue. Patients with high expression of RAD54L were associated with worse overall survival in the TCGA cohort and validation cohort. This study suggests a potential mechanism of lung cancer progression and provide a budding prognostic factor and treatment target in early-stage LUAD.

A number of long non-coding RNAs (lncRNAs) have been found to be involved in tumor progression and associated with disease prognoses in various types of cancer. Our study identified a novel three-lncRNA signature to predict survival of head and neck squamous cell caner (HNSCC) patients. We utilized The Cancer Genome Atlas (TCGA) cohort to screen out overall survival (OS)-associated lncRNAs in HNSCC and further developed a model to identify a lncRNA signature for evaluating disease status and prognosis. The lncRNA signature was then validated in HNSCC patients from our Fudan University Shanghai Cancer Center (FUSCC) cohort. LINC02434, AL139327.2, and AC126175.1 were identified by multivariable Cox regression analyses of independent risk factors for deceased status. We built a risk score model based on the three-lncRNA signature using coefficient of multivariable Cox regression and expression value of the three lncRNAs. The high-risk signature score was significantly associated with decreased OS in both the TCGA cohort and the FUSCC cohort. The high-risk group had worse overall survival than the low-risk group in TCGA cohort. To further validate the robustness of three-lncRNA signature risk score model developed in the TCGA dataset, the performance of risk score also evaluated in our institute FUSCC cohort. Additionally, the signature score showed a positive correlation with aggressive outcomes of HNSCC, such as III/IV stage, TP53 mutation, and PI3KCA mutation. The gene set enrichment analysis indicates that the risk score is associated with cancer metastasis-related pathways. Several cancer-related pathways, such as epithelial mesenchymal transition, TNFα signaling via NF-κB, MYC targets, and angiogenesis. The three-lncRNA signature could provide a novel prediction insight into the prognosis of HNSCC patients. The three-lncRNA signature was identified as a predictor of poor prognoses in HNSCC, which may serve as a potential therapeutic target.

ObjectivePrevious studies have shown that tumor mutation burden (TMB) in cancer is associated with prognosis. The purpose of this study is to identify TMB related genes in gastric cancer (GC) and to explore their prognostic value.MethodsIn our research, weighted gene coexpression network analysis (WGCNA) algorithm was used to cluster the most relevant TMB modules in the Cancer Genome Atlas (TCGA) database. Limma package was used to screen the differentially expressed genes, and the intersection was identified as hub genes. We used gene expression profiling interactive analysis (GEPIA) and survival algorithm to analyze the clinical characteristics and prognosis of hub genes in tumor and normal tissue samples of TCGA and Gene Expression Omnibus cohort respectively. We also used CIBERSORT algorithm to calculate the proportion of 22 tumor immune cells in the high and low expression subgroups of hub genes. In addition, we used gene set enrichment analysis (GSEA) to predict the biological function of hub genes. P < 0.05 was considered statistically significant.ResultsIn the TCGA cohort, TMB was significantly correlated with the clinical features of GC (P < 0.05). Through WGCNA and differential gene analysis, we identified SCN7A as the hub gene (P < 0.05, |log2fc|> 1, and mm > 0.8). We found that the expression of SCN7A in tumor tissues was lower than that in normal tissues, and its expression level was also related to overall survival rate and tumor stage. GSEA analysis showed that SCN7A low expression group was enriched with "DNA replication", "base extension repair" and "proteasome" gene sets in GC. In addition, we found that there were significant differences in the infiltration degree of 7 kinds of immune cells between the two groups.ConclusionTMB can indicate the prognosis of gastric cancer. SCN7A is a hub gene associated with TMB, and its low expression is associated with better prognosis.

MUC16, which encodes cancer antigen 125 (CA-125), is frequently mutated in gastric cancer (GC); however, its association with tumor mutation load (TML) and outcome in patients with GC has not been established, to date. To investigate whether MUC16 mutations are associated with TML and prognosis in patients with GC. Statistical analysis of genomic data from 437 GC samples obtained from The Cancer Genome Atlas (TCGA) and 256 samples from an Asian cohort. Both cohorts contained data of patients with GC involved in previous genomic studies. Data were obtained from TCGA on September 3, 2017, and from the Asian cohort on March 5, 2013, and analyzed from September 3 to December 1, 2017. The TCGA cohort was used as a discovery set and the Asian cohort as a validation set. Kaplan-Meier survival analysis and multivariate Cox and logistic regression models were applied. Regression models addressed confounding factors; Bayesian variant nonnegative matrix factorization was used to extract mutational signatures. The MutSigCV algorithm was used to identify significantly mutated genes. Primary outcomes were mutation frequency, overall survival, and TML, calculated using Kaplan-Meier survival analysis, odds ratios (ORs), and significance of signaling pathways. MUC16 was mutated in 168 of 437 (38.4%) of the GC samples from the TCGA cohort and in 57 of 256 (22.3%) from the Asian cohort. In both cohorts, GC samples with MUC16 mutations exhibited significantly greater TML than those without MUC16 mutations (median mutation counts: TCGA cohort, 264 with MUC16 mutation vs 115 without; Asian cohort, 134 with MUC16 mutation vs 74 without; Wilcoxon rank sum test, both P < .001). This association was independent of mutations in POLE and BRCA1/2 and mutational signatures in the TCGA cohort (OR, 1.87; 95% CI, 1.49-2.36; P < .001) and the Asian cohort (OR, 1.69; 95% CI, 1.25-2.29; P < .001). MUC16 mutations were significantly associated with better prognosis in both cohorts (median overall survival, 46.9 [95% CI, 26.4-NA (not available)] vs 26.7 [95% CI, 20.2-43.1] months; log-rank test, P = .007 [TCGA cohort] and not calculable [the median overall survival of patients with GC and MUC16 mutations could not be calculated because more than half the patients in the group were alive] vs 36.8 months; P = .04 [Asian cohort]). The association remained statistically significant after controlling for age, sex, TNM stage, mutations in POLE and BRCA1/2, and mutational signatures (hazard ratio, 0.61 [95% CI, 0.42-0.89]; log rank test, P = .01). Immune response and cell cycle regulation circuits were among the top altered signaling pathways in samples with MUC16 mutations (normalized enrichment score, 1.70 [95% CI, 1.57-1.79] and 2.04 [95% CI, 1.90-2.18]; adjusted P < .001). The prognostic significance of MUC16 mutation identified in the TCGA cohort was validated in the Asian cohort. These findings indicate that MUC16 mutations may be associated with higher TML, better survival outcomes, and immune response and cell cycle pathways. These findings may be immediately applicable for guiding immunotherapy treatment for patients with GC.

e17528 Background: Little information has been available regarding immune-related prognostic factors in patients with advanced hypopharyngeal squamous cell carcinoma (HPSCC). Expression of programmed cell death-ligand 1 (PD-L1) in tumor cells is known to be a mechanism whereby cancer can escape immune surveillance. We investigated the predictive relevance of PD-L1 expression in tumor cells and tumor-infiltrating lymphocyte (TIL) density in patients with locally advanced HPSCC receiving neoadjuvant chemotherapy (NAC). Methods: We retrospectively reviewed 83 consecutive patients with advanced HPSCC who had received NAC. PD-L1 expression and TIL density were evaluated by immunohistochemical analysis. Results: Univariate and multivariate analyses demonstrated that CD8+ TIL density was an independent and significant predictive factor for progression free survival (PFS) and overall survival (OS), whereas PD-L1 expression was not correlated with PFS or OS. Subgroup analysis defined by PD-L1 expression in combination with CD8+ TIL density revealed that the PD-L1-/CD8high group showed the longest survival (median PFS and OS were not reached), whereas the PD-L1+/CD8low group showed the shortest PFS (median 7.9 months, p = 0.006) and OS (14.3 months, p = 0.011) by Kaplan-Meier curves. Conclusions: Although there was no significant correlation between PD-L1 expression and prognosis in stage III and IV HPSCC patients who received NAC, the subgroup analysis indicated that combination of lack of PD-L1 expression and higher CD8+ TIL density was significantly associated with favorable survival in these patients. These results suggested that PD-L1 expression levels in combination with CD8+ TIL density could be a useful predictive biomarker in patients with stage III and IV HPSCC.

Tumor-associated Macrophage-derived Interleukin-23 Interlinks Kidney Cancer Glutamine Addiction with Immune Evasion

Background: Cancer stem cells (CSCs) are key drivers of tumorigenesis and metastasis. However, the precise roles of CSC-associated genes in these processes remain unclear. Methods: This study integrates cancer stem cell biomarkers and clinical data from The Cancer Genome Atlas (TCGA) specific to bladder cancer (BLCA). By combining differentially expressed genes (DEGs) from TCGA-BLCA samples with CSC-related biomarkers, we conducted comprehensive functional analyses and developed an 8-gene prognostic signature through Cox regression, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox regression. This model was validated with GEO datasets (GSE13507 and GSE32894), and the single-cell RNA seq dataset GSE222315 was subsequently analyzed to characterize the signature genes and elucidate their interactions. And a nomogram was created to stratify TCGA-BLCA patients into risk categories. The ‘oncoPredict’ algorithm based on the GDSC2 dataset assessed drug sensitivity in BLCA. Result: From the TCGA cohort, 665 CSC-related genes were identified, with 120 showing significant differential expression. The 8-gene signature (ALDH1A1, CBX7, CSPG4, DCN, FASN, INHBB, MYC, NCAM1) demonstrated strong predictive power for overall survival in both TCGA and GEO cohorts, as confirmed by Kaplan–Meier and ROC analyses. The nomogram, integrating age, tumor stage and risk scores, demonstrated high predictive accuracy. Additionally, the oncoPredict algorithm indicated varying drug sensitivities across patient groups. Based on retrospective data, we identified a novel CSC-related prognostic signature for BLCA. This finding suggests that targeting these genes could offer promising therapeutic strategies.